CN1738909A - Diagnosis of sepsis or SIRS using biomarker profiles - Google Patents

Abstract

The early prediction or diagnosis of sepsis advantageously allows for clinical intervention before the disease rapidly progresses beyond initial stages to the more severe stages, such as severe sepsis or septic shock, which are associated with high mortality. Early prediction or diagnosis is accomplished by comparing an individual's profile of biomarker expression to profiles obtained from one or more control, or reference, populations, which may include a population who develops sepsis. Recognition of features in the individual's biomarker profile that are characteristic of the onset of sepsis allows a clinician to diagnose the onset of sepsis from a bodily fluid isolated at the individual at a single point in time. The necessity of monitoring the patient over a period of time is, therefore, avoided, advantageously allowing clinical intervention before the onset of serious symptoms.

Description

Use biomarker spectrum diagnosis of sepsis or SIRS

The application requires the U.S. Provisional Patent Application sequence number 60/425 of submission on November 12nd, 2002, the U.S. Provisional Patent Application sequence number 60/511 that 322 right of priority and on October 17th, 2003 submit to, 644 right of priority, these two U.S. Provisional Patent Application are all incorporated into this paper as a reference by complete.

Invention field

The present invention relates to diagnose or predict the method for septicopyemia in the individuality or its developmental stage.The invention still further relates to the method for systemic inflammatory response syndromes in the diagnosis individuality.

Background of invention

More effective therapeutic treatment and corresponding more favourable clinical effectiveness are allowed in detecting in early days of morbid state usually.Yet, in many cases, disease symptoms detect existing problems in early days; So disease may become relative late period before may diagnosing.The systematicness inflammatory conditions is represented this disease of a class.These illnesss, especially septicopyemia, usually the interaction by pathogenic micro-organism and host's system of defense causes that this interacts and causes excessively and the Inflammatory response of dysregulation in the host.The complicacy of host response makes at the effort of understanding disease pathology intricate (Healy, the summary among the Annul.Pharmacother.36:648-54 (2002)) during the systematicness Inflammatory response.The incomplete understanding of disease pathology makes again finds that the diagnostic biomarker becomes difficult.Yet, because septicopyemia develops into life-threatening illness very fast, so press for early stage and reliable diagnostic.

Septicopyemia is followed a kind of clear and definite time history, and is positive in septicopyemia from systemic inflammatory response syndromes (" SIRS ")-feminine gender to SIRS-, and septicopyemia develops into serious septicopyemia, septic shock, multiple organ dysfunction unusual (" MOD ") then, and is final dead.When infected individuality subsequently SIRS takes place, also septicopyemia can appear in this individuality." SIRS " is generally defined as two or more that have following parameter: body temperature is greater than 38 ℃ or less than 36 ℃; Heart rate is greater than per minute 90 times; Respiration rate is breathed for 20 times greater than per minute; P _CO2Less than 32mmHg; With leukocyte count less than 4.0 * 10 ⁹Individual cell/L or greater than 12.0 * 10 ⁹Individual cell/L perhaps has greater than 10% immature band shape." septicopyemia " is generally defined as the SIRS with definite course of infection." serious septicopyemia " is unusual with MOD, ypotension, disseminated intravascular coagulation (" DIC ") or hypoperfusion, and it comprises the change of lactic acidosis disease, oliguresis and the mental status." septic shock " is generally defined as septicopyemia inductive ypotension, its anti-liquid resuscitation and exist hypoperfusion unusual.

Record has been proved to be difficulty to the existence of the important pathogenic micro-organism of septicopyemia clinically.Usually by cultivating patient's blood, phlegm, urine, wound exudate, intrinsic wire conduit surface, or the like detect pathogenic microorganism.Yet pathogenic microorganism may exist only in the microenvironment of some health, thereby the concrete material of being cultivated may not contain the contaminative microorganism.Can be owing to the few and feasible detection of microbe number that infection site exists is complicated more.The cause of disease number is given less by cultivating the blood diagnosis of sepsis and has been brought special problem in the blood sample.In a research, for example, only in 17% patient, obtain positive cultivation results (people such as Rangel-Frausto, JAMA 273:117-23 (1995) .) with septicopyemia clinical manifestation.Non-microbiological contamination sample can make diagnosis further complicated.For example, only 12.4% detected microorganism is important clinically in 707 septicemia patients' research.(people such as Weinstein, Clinical Infectious Diseases 24:584-602 (1997) .)

The difficulty of the early diagnosis of septicopyemia can be reflected by height morbidity and the high mortality with this disease-related.Current septicopyemia is the tenth main cause of death of the U.S. and general especially in the inpatient of non-crown intensive care unit (ICU) (ICUs), and septicopyemia is the modal cause of death in the intensive care unit (ICU).General mortality rate is estimated only in the U.S. 750,000 examples just to take place every year up to 35%.Only the year cost of U.S.'s treatment septicopyemia just is tens of dollars.

Therefore, need enough methods of early diagnosing and allow effectively to intervene and prevent septicopyemia.Most of existing septicopyemia marking systems or predictive model are only predicted the danger of the patient's middle and advanced stage complication (comprising death) that has been considered to septicopyemia.Yet these systems and model are not predicted the development of septicopyemia self.Especially need those patients are divided into and will suffer from septicopyemia or not suffer from the SIRS patient's of septicopyemia method.Current, the researchist defines single biomarker usually, the expression level difference of this biomarker in normal (that is non-septicopyemia) control group of septicopyemia patient group and patient.The u.s. patent application serial number 10/400,275 (its complete content is incorporated by reference) that on March 26th, 2003 submitted to discloses the method that discloses early stage septicopyemia by the variation of the dependence time in the expression level of analyzing various biomarkers.Therefore, diagnose the current expression that needs to detect multiple biomarker and monitor these biomarkers in for some time of the best approach of early stage septicopyemia.

Continue to press for special in this area and diagnosis of sepsis delicately, and do not need monitored patient in time.Ideally, diagnose by a kind of technology, this technology accurately, detect multiple biomarker simultaneously fast and at a time point, advancing of disease minimizes in the required time of diagnosis thereby make.

Summary of the invention

The present invention allows accurately by detect more than one biomarker from biological sample in a time point, fast and delicately prediction and diagnosis of sepsis.By at a time point from individuality, especially have and suffer from septicopyemia danger, suffer from septicopyemia, the individuality of suffering from septicopyemia perhaps under a cloud obtains the biomarker spectrum, and will compose with the reference biomarker from this individual biomarker spectrum and compare, and realizes this prediction and diagnosis.Can obtain reference biomarker spectrum from a group individuality (" reference colony "), these individualities for example are subjected to the torment of septicopyemia or suffer the septicopyemia outbreak or be in the specified phase of septicopyemia development.If contain the suitable characteristic features of composing from the biomarker of reference colony from this individual biomarker spectrum, this individuality is diagnosed as more and may equally with reference colony develops into septicopyemia, is subjected to the torment of septicopyemia or is in the specified phase that septicopyemia develops so.Also can obtain reference biomarker spectrum from various population of individuals, suffer from SIRS or infected those individualities that do not have SIRS but these colonies comprise.Therefore, the present invention allows the clinician to determine which patient does not suffer from SIRS, and but which is suffered from SIRS can not be at the time limit troubles septicopyemia of research, and which patient suffers from septicopyemia, and perhaps which is in the danger of final trouble septicopyemia.

Although method of the present invention especially can be used for detecting or predicting the outbreak of septicopyemia among the SIRS patient, but it will be appreciated by those skilled in the art that method of the present invention can be used for arbitrary patient, this patient includes, but not limited to the SIRS of suffering under a cloud or is in the patient in arbitrary stage of septicopyemia.For example, can gather biological sample from the patient, and the spectrum of the biomarker in this sample can be compared with several different reference biomarkers spectrums, each of these reference biomarker spectrums is from the patient who for example suffers from SIRS or be in the specified phase of septicopyemia.This patient's biomarker spectrum is categorized as corresponding to the figure from specific reference colony can predicts that this patient belongs in this reference colony.Based on diagnosis, can start suitable treatment plan from method gained of the present invention.

Be used to diagnose or predict that the existing method of SIRS, septicopyemia or septicopyemia development stages is based on non-specific clinical symptom and symptom; Therefore, the gained diagnosis has limited clinical efficacy usually.Because method of the present invention detects the various stages of septicopyemia exactly, so these methods can be used for identifying those individualities that may participate in treatment research aptly.Because can from the biological sample of single time point gained, predict or diagnosis of sepsis by " snapshot " of biomarker expression, so should treatment research can before serious clinical symptom appearance, begin.Because measure the biomarker spectrum of biological sample, so needn't identify concrete biomarker.Yet, the invention provides the method for biomarker-specific of the characteristic collection of illustrative plates of the specified phase of identifying septicopyemia or septicopyemia development.These biomarkers self will be the useful tools of prediction or diagnosis of sepsis.

Therefore, the invention provides the method for septicopyemia outbreak in the prediction individuality.These methods are included in single time point and obtain biomarker spectrum and biomarker spectrum that should individuality from individuality and compose with the reference biomarker and compare.The comparison of biomarker spectrum can be predicted the outbreak of septicopyemia in the individuality, and accuracy for predicting is at least 60%.Can before the septicopyemia outbreak, repeat this method any time once more.

The present invention also provide determine to suffer from or the individuality of suffering from septicopyemia under a cloud in the method for septicopyemia development, this method is included in single time point and obtains biomarker spectrum and biomarker spectrum that should individuality from this individuality and compose with the reference biomarker and compare.The comparison of biomarker spectrum can be diagnosed the septicopyemia in the individuality, and the accuracy of diagnosis is at least 60%.Can repeat this method to this individuality at any time.

The present invention also provide determine to suffer from or the individuality of suffering from septicopyemia under a cloud in the method for development (for example, stage) of septicopyemia.This method is included in single time point and obtains biomarker spectrum and biomarker spectrum that should individuality from this individuality and compose with the reference biomarker and compare.The comparison of biomarker spectrum can be measured the development of the septicopyemia in the individuality, and the accuracy of this mensuration is at least about 60%.Can repeat this method to this individuality at any time.

In addition, the invention provides that diagnosis suffers from or the individuality of the SIRS of suffering under a cloud in the method for SIRS.This method is included in single time point and obtains biomarker spectrum and biomarker spectrum that should individuality from this individuality and compose with the reference biomarker and compare.The comparison of biomarker spectrum can be diagnosed SIRS in the individuality, and the accuracy of this diagnosis is at least about 60%.Can repeat this method to this individuality at any time.

In another embodiment, the invention provides the method for determining septicopyemia state in the individuality or diagnosis SIRS, this method comprises the application decision rules.This decision rules comprises biological sample biomarker spectrum that produces and the biomarker spectrum that (i) produces from reference colony that comparison (i) is gathered from this individuality at single time point.Using this decision rules can determine the septicopyemia state in this individuality or diagnose SIRS.Can repeat this method to this individuality at one or more time points that separate, single.

The present invention also provides the method for septicopyemia state in definite individuality or diagnosis SIRS, and this method comprises that obtaining biomarker spectrum and biomarker spectrum that should individuality from this individuality composes with the reference biomarker and compare.Once this comparison just can be classified as this individuality the membership qualification with reference colony.Biomarker spectrum more also determined should individuality in state or the diagnosis SIRS of septicopyemia.

The present invention also provides the method for septicopyemia state in definite individuality or diagnosis SIR, and this method is included in from picking up from this individual biological sample and obtains biomarker spectrum and biomarker spectrum that should individuality and compose with the reference biomarker that obtains from the biological sample from reference colony and compare.Reference colony can be selected from normal reference colony, the positive reference of SIR-colony, the negative reference of infected/SIRS colony, the positive reference of septicopyemia colony, be in the reference colony of the development specified phase of septicopyemia, after about 0 to 36 hour, will be proved the positive reference of the SIR-colony of suffering from septicopyemia by routine techniques, after about 36-60 hour, will be proved the positive reference of the SIR-colony of suffering from septicopyemia by routine techniques, after about 60-84 hour, will be proved the positive reference of the SIR-colony of suffering from septicopyemia by routine techniques.Whether once this comparison just can be classified as this individuality is this reference group member, and this relatively determines septicopyemia state or diagnosis SIRS in this individuality.

In a further embodiment, the invention provides the method for determining septicopyemia state in the individuality or diagnosis SIRS.This method comprises relatively the detectable feature of biomarker that the biomarker spectrum that obtains from the biological sample of this individuality collection and biological sample from reference colony the obtain at least a biomarker between composing.Based on this relatively, this individuality is classified as and belongs to or do not belong to this reference colony.Therefore, this relatively determines septicopyemia state or diagnosis SIRS in this individuality.In one embodiment, these biomarkers are selected from the biomarker group shown in any that show 15-23 and 26-50.

In another embodiment, the invention provides the method for determining septicopyemia state in the individuality or diagnosis SIRS, this method comprises that one group of biomarker from the spectrum that the biological sample of individuality produces selects at least two kinds of features.These features are compared with one group of identical biomarker the spectrum that produces from the biological sample of reference colony.Whether once this comparison just can be classified as this individuality is this reference group member, and accuracy is at least about 60%, and this relatively determines septicopyemia state or diagnosis SIRS in this individuality.

The present invention also provides the method for septicopyemia state in definite individuality or diagnosis SIRS, this method comprise the abundance of determining at least two kinds of contained in individual biological sample biomarkers variation and should the sample of individuality in the biological sample of abundance and reference colony of these biomarkers the abundance of these biomarkers compare.Whether this comparison can be classified as this individuality is this reference group member, and this relatively determines septicopyemia state or diagnosis SIRS in this individuality.

In another embodiment, the invention provides the method for determining septicopyemia state in the individuality, this method comprises that the variation of determining with from the abundance of at least 1,2,3,4,5,10 or 20 kind of biomarker of the biological sample of the reference colony of suffering from septicopyemia and the reference colony of not suffering from septicopyemia compares the variation of the abundance of at least 1,2,3,4,5,10 or 20 kind of biomarker of this individuality.Biomarker is selected from listed biomarker in table 15-23 and any table of 26-50.Alternatively, at least 1,2,3,4,5,10 or the abundance of 20 kind of biomarker can compare with at least 1,2,3,4,5,10 or the abundance of 20 kind of biomarker.

The present invention also provides the method for separating bio mark, and septicopyemia can be diagnosed or predict to the existence of this biomarker in biological sample.This method comprises that obtain reference biomarker spectrum and identify from the colony of individuality can the prediction or the feature in one of diagnosis of sepsis or developing stage of septicopyemia this reference biomarker spectrum.This method also comprises to be identified and the corresponding biomarker of this feature, separates this biomarker then.

In another embodiment, the invention provides test kit, it contains at least 1,2,3,4,5,10 or all biomarkers that are selected from biomarker listed in table 15-23 and any table of 26-50.

In another embodiment, reference biomarker spectrum can contain at least two kinds of features, and preferred 5,10 or 20 or more kinds of combinations, wherein these features are that biomarker is peculiar in this sample.In this embodiment, these features will help to predict that this individuality is included in the specific reference colony.Can determine the Relative Contribution of these features in prediction comprises by the data analysis algorithm, this algorithm predicts class comprise the accuracy of (Class inclusion) be at least about 60%, at least about 70%, at least about 80%, at least about 90%, about 95%, about 96%, about 97%, about 98%, about 99% or about 100%.In one embodiment, combination of features allows the actual outbreak precontract 24, about 48 or the outbreak of about 72 hours prediction septicopyemias at the septicopyemia of determining by routine techniques.

In another embodiment, reference biomarker spectrum can contain at least two kinds of features, wherein at least one be corresponding biomarker peculiar and wherein this feature will allow the prediction individuality to be included in septicopyemia-positive or the SIRS-positive colony.In this embodiment, this feature is assigned with the p value, and this p value is from nonparameter test, and signed rank test obtains as Wilcoxon, this p value is directly related with the determinacy degree, uses this this feature of determinacy degree individual segregation can be become belong to the positive colony of septicopyemia-positive or SIRS-.In another embodiment, this feature becomes to belong to septicopyemia-positive or the positive colony of SIRS-with individual segregation, and the accuracy of classification is at least about 60%, about 70%, about 80% or about 90%.In a further embodiment, this feature allows the actual outbreak precontract 24, about 48 or the outbreak of about 72 hours prediction septicopyemias of the septicopyemia determined by routine techniques.

In a further embodiment, the invention provides the particulate array, these particle surfaces are stained with capture molecules, can specific combination be selected from biomarker listed in any table of table 15-23 and 26-50 at least 1,2,3,4,5,10 kind or all biomarkers.

The accompanying drawing summary

Fig. 1 illustrates the development of SIRS to septicopyemia.The illness of septicopyemia is made up of three phases at least, and it is unusual to multiple organ dysfunction that the septicopyemia patient develops into septic shock from serious septicopyemia.

Fig. 2 has shown the relation between septicopyemia and the SIRS.A plurality of set shown in Wien (Venn) figure are corresponding to the colony of the individuality with represented illness.

Fig. 3 has shown the positive colony of septicopyemia with respect to the positive colony of SIRS-, the natural logarithm of ratio in about 400 kinds of ionic average peak intensities.

Fig. 4 has shown that in the ESI-mass spectrum m/z is 437.2Da and at C ₁₈Retention time is 1.42 minutes an ionic intensity on the reversed-phase column.Fig. 4 A has shown the variation that the multiple colony intermediate ion of the individuality of suffering from septicopyemia exists.The clinical signs of suspected of septicopyemia took place in " time 0 " in the septicopyemia group, and this clinical signs of suspected detects by routine techniques." time-24 hour " and " time-48 hour " representative is the clinical signs of suspected precontract 24 hours of septicopyemia outbreak in the septicopyemia group and the sample of gathering in about 48 hours respectively.Individuality enters research in " sky 1 ".Fig. 4 B shows this identical ion of existence from the sample that the colony of the individuality of not suffering from septicopyemia 0 o'clock time gathers.

Fig. 5 be among 10 septicopyemia patients and 10 the SIRS patients since the classification tree of the data fitting of time 0, show three kinds of biomarkers identifying by electrospray ionization mass spectrum and distinguish that septicopyemia and SIRS are relevant.

Fig. 6 has shown the configuration of describing among the use embodiment, and the representative LC/MS and the LC/MS/MS that obtain from plasma sample compose.

Fig. 7 A and 7B have shown before changing into septicopyemia in blood plasma to be conditioned with higher level and have reached 48 hours protein.

Fig. 8 A and 8B have shown before changing into septicopyemia reached 48 hours protein with more low-level being conditioned in blood plasma.

DESCRIPTION OF THE PREFERRED

The present invention allows to utilize one or more biological samples that obtain from individuality in a time point (" snapshot ") or the process at disease progression to diagnose fast, sensitively and accurately or the prediction septicopyemia.Advantageously, can before the clinical symptom outbreak, diagnose or the prediction septicopyemia, thereby allow more effective treatment intervention.

" systemic inflammatory response syndromes " or " ISRS " refer to the clinical response to multiple serious clinical lesion, two or more of the situation below it shows as in 24 hours:

^*Body temperature is greater than 38 ℃ (100.4 °F) or less than 36 ℃ (96.8 °F);

^*Heart rate (HR) is greater than 90 times/minute;

^*Respiration rate (RR) is greater than 20 breaths/min, perhaps P _CO2Less than 32mmHg, perhaps need mechanical ventilation; With

^*Leukocyte count (WBC) is greater than 12.0 * 10 ⁹/ L or less than 4.0 * 10 ⁹/ L or greater than 10% prematurity form (band).

On behalf of the consistent of SIRS, these symptoms of SIRS define, and this is defined in and can be modified in the future or be replaced by the definition of improvement.This definition is used to illustrate current clinical practice and does not represent critical aspects of the present invention.

The patient who suffers from SIRS has clinical manifestation, it is classified as SIRS defined above, but is not considered to septicopyemia clinically.The individuality that is in the danger that septicopyemia takes place comprises the patient among the ICU and suffers the physiology wound, as the patient of burn or other damages." septicopyemia " refers to the positive illness of the SIRS-relevant with the course of infection that confirms.The suspection of the positive illness of the SIRS patient's that the clinical signs of suspected of septicopyemia is caused by course of infection SIRS-causes.Herein, " septicopyemia " comprises all stages of septicopyemia, includes, but not limited to outbreak, the serious septicopyemia and the MOD relevant with the latter stage of septicopyemia of septicopyemia.

" outbreak of septicopyemia " refers to the early stage of septicopyemia, that is, the clinical signs of suspected stage before of septicopyemia is enough supported in clinical manifestation.Use routine techniques to suspect septicopyemia before the time of septicopyemia because method of the present invention is used to detect, thus can only septicopyemia show clinically more obviously the time this disease of patient state confirm early stage septicopyemia retrospectively the time.The patient form septicopyemia really cutter reason be not critical aspects of the present invention.Method of the present invention can be independent of the variation in the origin detection of biological mark spectrum of course of infection.No matter how septicopyemia produce, method of the present invention all allows to determine to suffer from or suspects the patient's of the septicopyemia suffered from by the used criteria classification in front or SIR state.

" serious septicopyemia " refer to unusual with organ dysfunction, hypoperfusion unusual or the relevant septicopyemia of septicopyemia inductive ypotension.Hypoperfusion includes, but not limited to the rapid change of lactic acidosis, oliguresis or the mental status unusually." septic shock " refers to septicopyemia inductive ypotension, and it does not respond and show as the periphery ypotension for enough intravenous fluid stimulations." change the patient " and refer to the SIRS positive patient, this patient develops into the clinical signs of suspected of septicopyemia usually in the ICU retention period during being monitored." non-transformation patient " refers to the SIRS positive patient, and this patient does not develop into the clinical signs of suspected of septicopyemia usually in the ICU retention period during being monitored.

" biomarker " is almost any biological compound that is present in biological sample and can separates or detect this biological sample from this biological sample, as protein or its fragment, peptide, polypeptide, proteoglycan, glycoprotein, lipoprotein, sugar, lipid, nucleic acid, organic or inorganic chemical, natural polymer, and small molecules.In addition, biomarker can be complete molecule, and perhaps it can be the part of this complete molecule, and this part can have partial function or can be by for example, antibody or other specific combination protein identification., think that so this biomarker can provide information if but the context of detection of biomarker and this patient's given state is relevant as the specified phase of septicopyemia.This detectable aspect can comprise that for example, from existence, the shortage of this biomarker in this individual biological sample, perhaps concentration, and/or this biomarker exists as the part of biomarker spectrum.This detectable aspect of biomarker is defined as " feature " in this article.But feature can also be the ratio of two or more context of detection of biomarker, and these biomarkers for example can have or not have known identity." biomarker spectrum " comprises at least two kinds of these features, and wherein these features can be corresponding to identical or different classes of biomarker, as nucleic acid and sugar.Biomarker spectrum can also contain at least 3,4,5,10,20,30 or more kinds of feature.In one embodiment, it is hundreds of that biomarker spectrum contains, perhaps even thousands of kinds of features.In another embodiment, the biomarker spectrum contains at least a interior at least one detectable aspect of target.

" phenotype variation " is the detectable variation of the parameter relevant with patient's given state.For example, phenotype changes increase or the minimizing can comprise biomarker in the body fluid, and is wherein should variation relevant with the outbreak of septicopyemia or septicopyemia.But phenotype changes the variation of the context of detection of the given state that can also comprise this patient, but this variation is not the variation of the context of detection of biomarker.For example, the variation in the phenotype can comprise the detectable variation in body temperature, respiration rate, pulse, blood pressure or other physiological parameters.These variations can detect by the routine techniques that clinical observation and use technology personnel know to determine.Herein, " routine techniques " be based on the technology of phenotype variation to individual segregation, mustn't go to according to biomarker spectrum of the present invention by these technology.

" decision rules (Decision rule) " is the method that is used for patient's classification.This rule can be taked one or more forms as known in the art, as people such as Hastie, " TheElements of Statistical Learning; " Springer-Verlag (Springer, New York (2001)) form of institute's illustration in, the document is incorporated into this paper as a reference by complete.The biomarker analysis of the complex mixture of molecule in the sample has been produced the feature of data centralization.Can act on outbreak, the development of determining septicopyemia, the diagnosis of sepsis of the data set of feature with decision rules, perhaps diagnose SIRS with the prediction septicopyemia.

The application of decision rules does not need perfect classification.In one embodiment, classification can have at least about 90% or even higher determinacy.In other embodiments, this determinacy be at least about 80%, at least about 70% or at least about 60%., deterministic useful degree can become by concrete grammar according to the present invention." determinacy " is defined as the merchant of sum with the individual sum that is classified of the individuality of accurately being classified.Herein, " determinacy " refers to " accuracy ".The feature of classification also is its " susceptibility "." susceptibility " of classification relates to the current percentage ratio of being suffered from the septicopyemia patient of septicopyemia by evaluation." susceptibility " is defined as the merchant of true positives number and true positives and false negative sum in the art.Compare, " specificity " of this method is defined as correctly being accredited as the patient's who does not suffer from septicopyemia percentage ratio.That is, " specificity " relates to the merchant of true negative and true negative and false positive sum.In one embodiment, susceptibility and/or specificity be at least about 90%, at least about 80%, at least about 70% or at least about 60%.Can be used for the number of the feature of individual segregation being generally about 4 with enough determinacy.Yet according to the deterministic degree of being sought, characteristic number can be more or less, but in all situations, characteristic number is at least 1.In one embodiment, the individual characteristic number that is used to classify is optimised and allow with high determinacy individual segregation.

" state determine " of septicopyemia or SIRS comprises patient's biomarker spectrum classification detected the existence of septicopyemia among this patient or SIRS with (1) among the patient, and (2) predict the outbreak of septicopyemia among this patient or SIRS, or (3) detect the development of septicopyemia among the patient." diagnosis " septicopyemia or SIRS refer to identify or detect septicopyemia or SIRS among the patient.Because the present invention can detect septicopyemia more delicately before obvious observable clinical manifestation,, the evaluation of septicopyemia or detection detect the outbreak of septicopyemia as defined above so comprising.Promptly, " outbreak of prediction septicopyemia " refers to this patient's biomarker spectrum is classified as corresponding to composing from some individual biomarkers, these individualities just develop into septicopyemia or from infected state to septicopyemia (that is the infection of the SIRS that is accompanying) from the specified phase of SIRS from infecting to have." development detects " of septicopyemia or SIRS or " development is determined " refer to suffered from the patient's of septicopyemia or SIRS biomarker spectrum classification by diagnosis.For example, the biomarker classification that is diagnosed as the patient who suffers from septicopyemia can be comprised detect or determine that this patient is from septicopyemia to serious septicopyemia or to the development of the septicopyemia with MOD.

According to the present invention, obtain the biomarker spectrum by the sample that obtains from individuality and can diagnose or predict septicopyemia." obtain " referring to " having " herein.The present invention especially can be used for predicting and diagnoses septicopyemia in the individuality, and wherein this individuality suffers from infection, and perhaps even septicopyemia, but this patient also is not diagnosed as and suffers from septicopyemia, suspects and suffer from septicopyemia, perhaps is in the danger that septicopyemia takes place.The present invention can be used for detecting and diagnosing SIRS in the individuality in an identical manner.That is, the present invention can be used to confirm the clinical signs of suspected of SIRS.The present invention also can be used for detecting a plurality of stages of septicopyemia process, such as infection, microbemia, septicopyemia, serious septicopyemia, septic shock, or the like.

To compose from the biomarker that individuality obtains, that is, biological subject mark spectrum is composed to comparing with the reference biomarker.This biomarker spectrum can be from colony's generation of body or two or more individualities one by one.This colony for example can contain 3,4,5,10,15,20,30,40,50 or more a plurality of body.In addition, if tried to produce and mutual the comparison from the biological sample of gathering in different time points with reference figure, reference biomarker spectrum and individual (examination) biomarker of being compared are so in the methods of the invention composed and can be produced from same individual.For example, can when beginning, the research phase obtain sample from individuality.The biomarker spectrum that the reference biomarker spectrum that obtains from this sample then can produce with the sample subsequently from this same individuality is compared.Thisly relatively can be used for, for example, determine this individual septicopyemia state by repeating in time to classify.

The individuality that reference colony can be selected from does not have SIRS (" SIRS-feminine gender "), do not have SIRS but experience course of infection individuality, suffer from SIRS but do not exist the individuality of septicopyemia (" the SIRS-positive "), the individuality of suffering from the outbreak of septicopyemia, septicopyemia positive and be in the individuality of one of septicopyemia development stages, the individuality that perhaps has the physiology wound that increases the danger that septicopyemia takes place.In addition, reference colony can be the SIRS-male and use the routine techniques diagnosis of sepsis subsequently.For example, be used to produce reference figure the SIRS-positive patient colony can in order to produce reference figure after these patients gather biological sample about 24,48,72,96 or more hours after be diagnosed as septicopyemia.In one embodiment, use routine techniques after about 0-36 behind the biological sample collection hour, about 36-60 hour, about 60-84 hour or about 84-108 hour, the mass diagnosis of SIRS-positive individuals to be septicopyemia.If this biomarker spectrum can indicate one of septicopyemia or its developmental stage, begin treatment before the clinician just can show in the clinical symptom of septicopyemia so.Treatment generally includes checks that this patient is to determine the source of infection.In case located the source of infection, the clinician will obtain culture from infection site usually, and this is preferably in empirical antimicrobial therapy that begins to be correlated with and auxiliary therapy measure that may be extra, as discharging abscess or removing before the infected conduit.The therapy of septicopyemia is summarized in Healy (as preceding).

Method of the present invention comprises that the biomarker spectrum with individuality compares with reference biomarker spectrum.Herein, " comparison " comprise distinguish individual and the reference biomarker compose at least one place diverse ways.Thereby, relatively can comprise, and relatively can comprise comparison on the arithmetical and statistics of the feature of distributing to figure by visual inspection chromatography collection of illustrative plates.This statistics relatively includes, but not limited to use decision rules.If the biomarker spectrum contains at least a interior mark, can also comprise target feature in these in order to the comparison of distinguishing the difference in the biomarker spectrum so, thereby the feature of biomarker is relevant with interior target feature.This relatively can predict the chance that obtains septicopyemia or SIRS; Perhaps this comparison can alleged occurrence or is not had septicopyemia or SIRS; Perhaps this comparison can be pointed out the stage of individual residing septicopyemia.

Therefore, the present invention need be in the supervision phase enforcement time-intensive mensuration, do not need to identify every kind of biomarker yet.Although the present invention does not need the supervision phase to individual segregation, should be appreciated that the classification that repeats to this individuality, promptly repeat snapshot, can carry out up to this individuality no longer on the line in time.Alternatively, the biomarker spectrum that obtains from this individuality can with the comparing of the one or more biomarkers spectrums that obtain from this same individual in different time points.The technician will understand that each comparison of making can both classify as this individuality the member in the reference colony in repeating assorting process.

Can distinguish the individuality of multiple physiological situation with a plurality of stages of developing corresponding to septicopyemia from no septicopyemia to MOD by characteristic biomarker spectrum.Herein, " individuality " is animal, preferred mammal, more preferably people or non-human primates.Term " individuality ", " experimenter " and " patient " are used interchangeably in this article.Individuality can be SIRS of suffering from normal, under a cloud or septicopyemia, be in the danger of suffering from SIRS or septicopyemia, perhaps be proved and suffer from SIRS or septicopyemia.Although there are many known biomarkers relevant with the development of septicopyemia, not all these marks all occur at initial preclinical phase.In fact, only can be by determine the subclass of the characteristic biomarker of early stage septicopyemia from the retrospective analysis of the individual gained sample of the clinical symptom of final performance septicopyemia.Be not bound by theory, can cause physiological change yet, embody in the specific change of these physiological change in biomarker is expressed even cause the initial pathology of septicopyemia to infect.For example, in case determined the characteristic biomarker spectrum in septicopyemia stage, just the biomarker spectrum of the biological sample that obtains from individuality can be composed to compare whether also be in that specified phase of septicopyemia with definite this experimenter with this reference.

Colony from a stage development of septicopyemia to another stage, perhaps (promptly from normality, feature is not suffer from the state of septicopyemia or SIRS) be change in the biomarker spectrum to septicopyemia or SIRS and the feature that vice versa, because some biomarker spectrum is reduced with the expression of higher horizontal expression and other biological mark.These variations in the biomarker spectrum can reflect that reference colony is to the gradual foundation in the physiologic response of for example infection and/or inflammation.The technician will understand that along with the disappearing of physiologic response the biomarker of reference colony spectrum also will change.As mentioned above, an advantage of the invention is to use individuality is classified as member in the special group from the biomarker of single biological sample spectrum.Yet the technician will understand by the classification subsequently to this individuality can help to determine that specific physiologic response is established or disappears.For this reason, the invention provides multiple biomarker, the increase that the expression level of these biomarkers has when the physiologic response to septicopyemia or SIRS is established or disappears, the reduction that has.For example, the researchist can select a kind of feature of individual biomarker spectrum, and is known along with the intensity of setting up this feature to the physiologic response of septicopyemia changes.Can determine that from the comparison of same characteristic features in the spectrum of the biological sample subsequently of this individuality this individuality is whether to more serious septicopyemia development or developing to normality.

The molecule identity of biomarker is not required in this invention.In fact, the biomarker of having identified before the present invention should not be limited to (see u.s. patent application serial number 10/400,275, on March 26th, 2003 submitted to).Therefore, expection will be identified new biomarker, and these biomarkers are given population of individuals, and the colony that one of special septicopyemia is early stage is peculiar.In one embodiment of the invention, identify also isolating biomarker.This biomarker is used to produce the antibody of specific combination then, and this antibody can promote the biological markers detection in the multiple diagnostic assay.For this reason, can use can be in conjunction with any antibody, antibody fragment or the derivative (for example, Fab, Fv or scFv fragment) of biomarker molecule in arbitrary immunoassay.These immunoassay are to know in this area.If this biomarker is an albumen, so can be with proven technique with its order-checking and clone its encoding gene.

Method of the present invention can be used for screening, for example, and the patient that ICU admitted.When admitting, gather biological sample immediately, for example, blood.The complex mixture of protein and other molecules is broken down into the biomarker spectrum in the blood.This can realize that this technology can reproducibly be distinguished these molecules based on certain physics or chemical property by the combination of using arbitrary technology or technology.In one embodiment, molecule is fixed on the matrix, separates by the mastrix-assisted laser desorption ionization time of flight mass spectrum then and distinguishes these molecules.Produce wave spectrum by the characteristic desorption mode, this interpretive model has reflected each molecule or its segmental mass ratio.In another embodiment, biomarker is selected from the multiple mRNA kind that obtains from cell extract, and obtains figure by mRNA kind and cDNAs hybridization array that should individuality.The diagnostic uses of cDNA array is to know (seeing that for example, Zou waits the people, Oncogene 21:4855-4862 (2002)) in this area.In a further embodiment, unite use protein and separate nucleic acid method and can obtain collection of illustrative plates.

The present invention also provides test kit, and this test kit can be used for determining the state or the diagnosis SIRS of septicopyemia in the individuality.Test kit of the present invention contains at least a biomarker.Being used for biomarker-specific of the present invention provides in this article.The biomarker of this test kit can be used for producing according to biomarker spectrum of the present invention.Other example of compounds includes, but not limited to protein, its fragment, peptide, polypeptide, proteoglycan, glycoprotein, lipoprotein, carbohydrate, lipid, nucleic acid, organic and inorganic chemical and natural and synthetic polymkeric substance in the test kit.This biomarker can be the part of array, and perhaps this biomarker can be separated and/or pack individually.This test kit can also contain at least a interior mark, and mark is used to produce biomarker spectrum of the present invention in this.Equally, interior mark can be above-mentioned any compounds category.Test kit of the present invention can also contain reagent, and this reagent can be used for detecting biomarker contained in the ground mark biological sample, and wherein the biomarker spectrum produces from this biological sample.For this reason, test kit can contain one group of antibody or their function fragment, these antibody or their function fragment in conjunction with below list biomarker given in any table of table of biomarker at least 2,3,4,5,10,20 or more kinds of.Antibody self can be detected ground mark.Test kit can also contain special biomarker in conjunction with component, as being fit to body (aptamer).If biomarker contains nucleic acid, test kit can provide oligonucleotide probe so, and this probe can form duplex with the complementary strand of this biomarker or biomarker.Oligonucleotide probe can detected ground mark.

When biomarker was used to produce antibody, test kit of the present invention can also comprise drug excipient, thinner and/or adjuvant.The example of medicine adjuvant includes, but not limited to sanitas, moistening agent, emulsifying agent, and dispersion agent.By comprising multiple antibacterium and anti-mycotic agent, for example, p-Hydroxybenzoate, chlorobutanol, phenol Sorbic Acid or the like can guarantee to prevent action of microorganisms.May also wish to comprise isotonic agent, as sugar, sodium-chlor, or the like.By reagent such as aluminum monostearate and the gelatin that comprises delayed absorption, the absorption that can prolong injectable medicament forms.

Generation biomarker spectrum

According to an embodiment, method of the present invention comprises that obtaining biomarker from the biological sample from the individuality collection composes.Biological sample can be blood, blood plasma, serum, saliva, phlegm, urine, cerebrospinal fluid, cell, cell extract, tissue sample, biopsy, faecal samples, or the like.For example, can obtain reference biomarker spectrum from the colony of individuality, these individualities are selected from SIRS-negative individuals, SIRS-positive individuals, suffer from the individual of septicopyemia outbreak and suffered from the individuality of septicopyemia.Can as infection, microbemia, serious septicopyemia, septic shock or MOD, have been suffered from the reference biomarker spectrum of the individuality of septicopyemia in arbitrary stage of septicopyemia development.

In one embodiment, can produce biomarker spectrum with separation method, thus the subclass of biomarker in the analytic sample only.For example, the biomarker of analyzing in sample can be made up of the mRNA kind from cell extract, this cell extract is the biological nucleic acid mark in the sample by fractional separation and only, perhaps biomarker can be made up of the part of proteinic total complement in the sample, described protein by chromatographic technique by fractional separation.Alternatively, can produce the biomarker spectrum without separation method.For example, can inquire (interrogate) biological sample with tagged compound, the biomarker in this tagged compound and the sample forms special mixture, and wherein the intensity of mark is the detectable feature of this biomarker in this special mixture.The compound that is suitable for forming this special mixture is the antibody that is labeled.In one embodiment, use and to have the antibody test biomarker that the nucleic acid that can increase serves as a mark.In a further embodiment, when two kinds of antibody (every kind of chain that is conjugated to nucleic acid marking) interacted with biomarker, this nucleic acid marking became and can be amplified, thereby two nucleic acid chains form the nucleic acid that can increase.

In another embodiment, the biomarker spectrum can be from mensuration, and as the mensuration of nucleic acid, wherein biomarker is nucleic acid or their complement.For example, biomarker can be a Yeast Nucleic Acid.The method that use is selected from nucleus magnetic resonance, nucleic acid array, dot blotting, slot blot, post transcription cloning and rna blot analysis can obtain the biomarker spectrum.In another embodiment, by the reactive antibody special to this biomarker, perhaps the function fragment of this antibody is by this biomarker spectrum of immunology detection.The function fragment of antibody is the fragment of antibody, and it keeps at least in conjunction with the antigenic certain ability of complete antibody institute bonded.This fragment includes, but not limited to scFv fragment, Fab fragment and F (ab) 2 fragments, and these fragments can produce by recombination method or enzyme.In another embodiment, be different from the specific combination molecule of antibody,, can be used in conjunction with this biomarker as being fit to body.In a further embodiment, but biomarker spectrum can contain the context of detection of infectious agent or its component.In a further embodiment, but the biomarker spectrum can contain micromolecular context of detection, and these small molecules can comprise the fragment of protein or nucleic acid, perhaps can comprise metabolite.

Use one or more separation methods can produce the biomarker spectrum.For example, suitable separation method can comprise mass spectrometry method, as desorb/ionization (DIOS) on electrospray ionization mass spectrometry (ESI-MS), ESI-MS/MS, ESI-MS/ (MS) (n is the integer greater than 0), the auxiliary laser desorption ionisation flight time mass spectrum of matrix (MALDI-TOF-MS), surperficial laser enhanced desorb/ionization time of flight mass spectrometry (SELDI-TOF-MS), the silicon, secondary ion massspectrum (SIMS), four utmost point flight time (Q-TOF), atmospheric pressure chemical ionization mass spectrum (APCI-MS) ⁿ, APCI-MS/MS, APCI-(MS), normal atmosphere Photoionization Mass Spectrometry (APPI-MS), APPI-MS/MS, and APPI-(MS) ⁿOther mass spectrometry methods can comprise four utmost points, Fourier transform mass spectrum (FTMS) and ion trap.Other suitable separation methods can comprise chemical extraction distribution, column chromatography, ion exchange chromatography, hydrophobic (anti-phase) liquid chromatography(LC), isoelectrofocusing, one dimension polyacrylamide gel electrophoresis (PAGE), two-dimentional polyacrylamide gel electrophoresis (2D-PAGE) or other chromatographies, as thin layer, gas phase or liquid chromatography (LC), perhaps their combination.In one embodiment, biological sample can be by fractional separation before using separation method.

The method of the physical sepn by not needing biomarker self also can produce the biomarker spectrum.For example, can use nucleus magnetic resonance (NMR) Wave Spectrum to differentiate the biomarker spectrum from the complex mixture of molecule.With NMR to the similar applications of staging at for example Hagberg, open among the NMRBiomed.11:148-56 (1998).Extra method comprises nucleic acid amplification technologies, and these technology can be used for producing biomarker spectrum and without each biomarker of physical sepn.(for example seeing people such as Stordeur, J.Immunol., people such as Methods 259:55-64 (202) and Tan, Proc.Nat ' l Acad.Sci.USA 99:11387-11392 (2002)).

In one embodiment, use the mastrix-assisted laser desorption ionization time of flight mass spectrum to produce the biomarker spectrum, wherein biomarker is protein or protein fragments, and they are by incidenting laser radiation ionization or from fixedly upholder evaporation.By every kind of proteic characteristic flight time generation collection of illustrative plates, this characteristic flight time is depended on its mass-to-charge ratio (" m/z ").Multiple laser desorption/ionization technique also is as known in the art.(see, for example, people such as Guttman, people such as Anal.Chem.73:1252-62 (2001) and Wei, Nature 399:243-46 (1999)).

The mastrix-assisted laser desorption ionization time of flight mass spectrum allowed to produce bulk information in the short relatively time limit.Biological sample is applied to one of multiple support, and this support is in conjunction with all biomarkers in the sample, the perhaps subclass of these biomarkers.Cell lysate or sample are applied directly to these surfaces with few volume to 0.5 μ L, these cell lysates or sample by or not by purifying or fractional separation in advance.Lysate or sample can be concentrated or dilute on being applied to the support surface time.In lacking, produce the mass spectrum of this sample then to 3 hours with laser desorption/ionization.

In another embodiment, measured total mRNA from this individual cell extract, and will be from the multiple mRNA kind of this biological sample gained as biomarker.For example, use standard method as known in the art, by these mRNA and probe array hybridization can be obtained collection of illustrative plates, this probe array can contain oligonucleotide or cDNA.Alternatively; mRNA can be implemented gel electrophoresis or trace method; as dot blotting, slot blot or rna blot analysis, all these methods all are as known in the artly (to see, for example; people such as Sambrook; " Molecular Cloning, the third edition ", Cold Spring HarborLaboratory Press; Cold Spring Harbor, New York (2001)).By reverse transcription, also can obtain mRNA figure as disclosed amplification of people such as Stordeur (as preceding) and detection gained cDNA then.In another embodiment, use combined method,, can obtain this figure as nucleic acid array and mass spectral combination.

The use of data analysis algorithm

In one embodiment, individual biomarker spectrum and reference biomarker spectrum relatively comprises the application decision rules.This decision rules can comprise the data analysis algorithm, as the computer patterns recognizer.Other suitable algorithms include, but not limited to the logistic regression or the nonparametric algorithm (for example, Wilcoxon has the rank test of symbol) of the difference in can the distribution of detected characteristics value.Decision rules can be based on l, 2,3,4,5,10,20 or more kinds of feature.In one embodiment, decision rules is based on hundreds of or more features.Use decision rules and also can comprise use classification tree algorithm.For example, reference biomarker spectrum can contain at least three kinds of features, and wherein these features are the predictors in the classification tree algorithm.Membership qualification in the data analysis algorithm predicts colony (perhaps class), its accuracy be at least about 60%, at least about 70%, at least about 80% with at least about 90%.

Suitable algorithm is as known in the art, and some algorithms were summarized in (as preceding) such as Hastie.These algorithms will be classified individuality is divided into characteristic biomarker expression level normal or that have specific morbid state as the complex spectrum of blood sample from biological material.Although these algorithms can be used for increasing speed and the efficient of using decision rules and avoiding researchist's bias, those skilled in the art will recognize that does not need the computer based algorithm to implement method of the present invention.

No matter be used to produce the method for biomarker spectrum, can use relatively biomarker spectrum of algorithm.For example, the biomarker that suitable algorithm can be applicable to use gas-chromatography to produce is composed, and as Harper. " Pyrolysis and GC in Polymer Analysis " Dekker, is discussed among the New York (1985).In addition, people such as Wagner, Anal.Chem 74:1824-35 (2002) discloses a kind of algorithm, and this algorithm has improved based on the ability of the spectrum that obtains by static flight time secondary ion massspectrum (TOF-SIMS) to individual segregation.In addition, people such as Bright, J.Microbiol.Methods 48:127-38 (2002) disclose by analyzing MALDI-TOF-MS spectrum and have distinguished the method for bacterial strain system with high determinacy (the correct classification rate of 79-89%).Use MALDI-TOF-MS has been discussed for Dalluge, Fresenius J.Anal.Chem.366:701-11 (2000) and liquid chromatography-electrospray ionization mass spectrometry (LC/ESI-MS) is classified to biomarker spectrum in the complex biological sample.

Biomarker

Can implement method of the present invention by producing the biomarker spectrum, septicopyemia or SIRS can be diagnosed or predict to these biomarker spectrums.Because collection of illustrative plates produces enough enforcement the present invention, needn't be known or identified subsequently so form the biomarker of this collection of illustrative plates.

Known those biomarkers that provide about the information of replying immune state in the infection can be provided the biomarker that can be used for producing biomarker spectrum of the present invention; Yet these biomarkers always do not provide information comparably.These biomarkers can comprise hormone, autoantibody, soluble and insoluble acceptor, somatomedin, transcription factor, cell surface marker and soluble mark, these biomarkers are from the host or from cause of disease self, as coat protein, lipopolysaccharides (intracellular toxin), lipoteichoic acid, or the like.The other biological mark includes, but are not limited to, and cell surface protein is as CD64 albumen; CD11b albumen; HLA II quasi-molecule comprises HLA-DR albumen and HLA-DQ albumen; CD54 albumen; CD71 albumen; CD86 albumen; The Tumor Necrosis Factor Receptors of surface bonding (TNF-R); The acceptor of pattern recognition acceptor such as similar Toll; Soluble mark such as interleukin I L-I, IL-2, IL-4, IL-6, IL-8, IL-10, IL-11, IL-12, IL-13 and IL-18; Tumor necrosis factor alpha (TNF-α); Mopterin; C-reactive protein (CRP); Procalcitonin (PCT); 6-ketone F1 α; Thromboxane B ₂Leukotriene B4, C3, C4, C5, D4 and E4; IFN-(IFN γ); α/interferon-(IFN α/β); α lymphotoxin (LT α); Complement component (C '); Platelet activation factor (PAF); Bradykinin, nitrogen protoxide (NO); CM-CSF (GM-CSF); Macrophage inhibition factor (MIF); Interleukin-1 receptor antagonist (IL-1ra); Soluble tumor necrosis factor receptor (sTNFr); Soluble interleukin-6 receptor sIL-1r and sIL-2r; Transforming growth factor-beta (TGF β); PGE ₂(PGE ₂); Granulocyte-G CFS (G-CSF); With other inflammatory mediators.(people such as Oberholzer, people such as Shock 16:83-96 (2001) and Vincent, people such as " The Sepsis Text, " Carlet, editor, summary in (KluwerAcademic Publishers, 2002)).Usually also be the candidate that is used for biomarker of the present invention with relevant with microbemia clinically biomarker, condition is that these biomarkers take place in biological sample usually and often.Biomarker can comprise low-molecular weight compound, and they can be the fragments of protein or nucleic acid, and perhaps they can comprise metabolite.Low-molecular weight compound can the reflection phenotype variation relevant with septicopyemia and/or SIRS as the existence or the concentration of metabolite.Particularly, the variation of the concentration of small molecular weight biomarker with reply SIRS and/or septicopyemia process in the variation of the cellular metabolism that produces of any physiological change relevant, these physiological change are such as hypothermia or high fever, heart rate or respiration rate increase, tissue hypoxia, metabolic acidosis or MOD.Biomarker can also comprise the RNA and the dna molecular of coded protein biomarker.

Biomarker can also comprise with white corpuscle to be regulated, as neutrophil activation or the relevant at least a molecule of monocyte inactivation.The expression increase of CD64 and CD11b is considered to the signal of neutrophilic granulocyte and monocyte activation.(people such as Oberholzer is as people such as preceding and Vincent, as summary in preceding).Can be used for those biomarkers of the present invention and comprise the biomarker relevant, (see people such as Gognon, Cell 110:119-31 (2002) as the mark of cytokine metabotic change with the scavenger cell split product; Oberholzer waits the people, as preceding; Vincent waits the people, as preceding).

Biomarker can also comprise known participation or be found the signal factor that participates in inflammatory process.Signal factor can start cascade of events in the cell, comprises the variation of activation, genetic transcription and/or translation skill of kinase whose activation in receptors bind, receptor activation, the cell, transcription factor and the variation of metabolic process, etc.For the purposes of the present invention, the signaling molecule of these molecule activations all is defined as " biomolecules relevant with the septicopyemia approach " with process.Relevant predictability biomarker can comprise the biomolecules relevant with the septicopyemia approach.

Therefore, although method of the present invention can use no inclined to one side method to identify the predictability biomarker, the clear particular group with physiologic response or the biomarker relevant with multiple signal pathway of technician can be the concrete theme of concern.This is especially like this for following situation: from the biomarker of biological sample and array (for example, antibody array or nucleic acid array) contact, wherein this array can be by being used to detect the amount of multiple biomarker with the direct and special interaction of biomarker.In this case, the array components selection can be based on following prompting, and the state of septicopyemia or SIRS is definite relevant in promptly concrete approach and the individuality.Specific biological molecules have can prediction or the indication of the feature of diagnosis of sepsis or SIRS can cause being expected at the other biological molecule that is conditioned in consistent mode on the physiology prediction or diagnostic characteristic can be provided equally.Yet the technician will understand, because this expection of complicacy of biosystem may not be implemented.For example, if the amount of specific mRNA biomarker is the predictability feature, if being expressed on the level of translation back of another biomarker is conditioned, the consistent variation during the mRNA of this another biomarker expresses so may not be detected.In addition, the mRNA expression level of biomarker can be subjected to the influence of multiple convergence approach, and these approach can be with relevant to the physiologic response of septicopyemia or irrelevant.

Can obtain biomarker from arbitrary biological sample, as an example but do not limit, this biological sample can be blood, blood plasma, saliva, serum, urine, cerebrospinal fluid, phlegm, ight soil, cell and cell extract, perhaps the other biological fluid sample, from host or patient's tissue sample or biopsy sample.Can be different from the definite biological sample of individual gained, but the preferred invasive of sampling is minimum and implement by routine techniques easily.

Can implement the detection that phenotype changes by arbitrary routine techniques.Can realize the detection of body temperature, respiration rate, pulse, blood pressure or other physiological parameters by clinical observation and detection.The detection of biomarker molecule can comprise, for example, points out to exist, the detection of concentration, expression level or any other value relevant with the biomarker molecule.The test format of biomarker molecule depends on the method that is used for forming from biological sample these biomarker spectrums usually.For example, dye can detect by 2D-PAGE by Coomassie blue stain or by silver and divide the biomarker open, described dyeing process is sophisticated in this area.

Separate useful biomarker

Expect that useful biomarker does not also have to identify or the biomarker relevant with the relevant physiological state with comprising.In one aspect of the invention, useful biomarker is accredited as the component of composing from the biomarker of biological sample.This evaluation can be implemented by the method that any is known in this area, and this method comprises immunoassay or automatization micrometering preface.

In case identified useful biomarker, just can separate this biomarker by one of many separation methods of knowing.Therefore, the invention provides separation and can diagnose or predict the method for the biomarker of septicopyemia, this method comprises that obtaining the reference biomarker from the colony of individuality composes, evaluation can prediction or a kind of feature of the reference biomarker spectrum of one of diagnosis of sepsis or septicopyemia developmental stage, identify and the corresponding biomarker of this feature, and separate this biomarker.In case separate, for example, if this biomarker is an albumen, this biomarker just can be used for producing the antibody in conjunction with this mark so, if this biomarker is a nucleic acid, this biomarker can be used for developing special oligonucleotide probe so.

The technician will understand easily can further characterize useful feature to determine the molecular structure of this biomarker.By this way the method for characterising biological molecule be know in this area and comprise high resolution mass spec, infrared spectra, ultraviolet spectrometry and nucleus magnetic resonance.Determine that the nucleotide sequence of nucleic acid biomarker, the aminoacid sequence of polypeptide biomarker and the composition of sugared biomarker and the method for sequence are to know in this area.

The present invention is applied to SIRS patient

In one embodiment, the method for current description is used to screen the SIRS patient who especially is in the danger of suffering from septicopyemia.Gather biological sample from the SIRS positive patient, and biomarker spectrum in this sample is compared with reference figure from the SIRS-positive patient that finally develops into septicopyemia.This patient's biomarker is composed the reference figure that is classified into corresponding to the positive colony of the SIRS-that develops into septicopyemia can diagnose this SIRS-positive patient will develop into septicopyemia equally.Can start treatment plan then to stop or to prevent the development of septicopyemia.

In another embodiment, the method for current description is used to confirm that the patient suffers from the clinical signs of suspected of SIRS.In this case, with biomarker spectrum in the sample with suffer from SIRS or do not suffer from SIRS individuality reference colony relatively.This patient's biomarker spectrum classified as corresponding to a colony or another colony can be used to diagnose this individuality to suffer from SIRS or do not suffer from SIRS.

Embodiment

The following examples are representatives of the included embodiment of the present invention and never limit the included theme of the present invention.

Embodiment 1: use quantitative liquid chromatography (LC)/electrospray ionization mass spectrometry (LC/ESI-MS) to identify the small molecules biomarker

1.1 the sample of accepting and analyzing

For two colonies of patient set up reference biomarker spectrum.First colony (" SIRS group ") representative suffers from SIRS and enters this research does not still develop into septicopyemia in their while in hospital 20 patients in " sky 1 ".Second colony (" septicopyemia group ") TYP suffers from SIRS and enters the patient who develops into septicopyemia after a couple of days is at least studied in this research but entering in sky 1.Per approximately 24 hours from each study group's blood sample collection.The clinical signs of suspected of septicopyemia took place in " time 0 " in the septicopyemia group, and this clinical signs of suspected detects by routine techniques." time-24 hour " and " time-48 hour " represent the clinical signs of suspected precontract 24 hours of septicopyemia outbreak in the septicopyemia group and the sample of gathering in about 48 hours respectively.That is, be included in and enter research same day the sample of gathering on clinical signs of suspected same day (time 0) of preceding 24 hours of the clinical signs of suspected (time-24 hour) of preceding 48 hours of clinical signs of suspected (time-48 hour), the septicopyemia of (day 1), septicopyemia and septicopyemia outbreak from the sample of septicopyemia group.Be divided into and analysed 160 blood samples: 80 samples are from 20 patients of septicopyemia group, and other 80 samples are from 20 patients of SIRS group.

1.2 specimen preparation

In blood plasma, many kinds of small molecules can be incorporated into protein, and this can reduce by the detected micromolecular quantity of pattern-production method.Therefore, remove most protein from plasma sample, discharging then can be in conjunction with these proteinic small molecules.Remove proteinic proper method and include, but not limited to ice-cold methyl alcohol, acetonitrile (CAN), butanols, perhaps trichoroacetic acid(TCA) (TCA) extraction blood plasma or thermally denature or acid hydrolysis.In this example, ice-cold methanol extraction blood plasma.Particular methanol extraction is because it causes detecting the small molecules of high number.Get 100% methanol mixed of 50 μ L and 100 μ L ice precooling from every kind of plasma sample, the final volume percentage ratio of methyl alcohol is 67%.With this solution vortex mixed 60 seconds.Then sample was hatched 20 minutes at 4 ℃, by with 12, centrifugal 10 minutes protein precipitations of 000rpm.Remove supernatant liquor, be dried, and be resuspended in the 50 μ L water.Before LC/MS analyzes, add two kinds of low-molecular-weight molecules to the plasma sample that is extracted: nefrosulfin pyridazone and stearylamine.These molecules are as making the standardized interior mark of ionic strength and retention time.The m/z of nefrosulfin pyridazone is 285.0Da (determining by MS), at 44%ACN place wash-out (determining by LC); The m/z of stearylamine is 270.3Da, at 89%ACN place wash-out.

1.3LC/ESl-MS molecule

The resuspended supernatant liquor of 10 μ L is expelled to 2.1 * 100mm C ₁₈Waters SymmetryLC post (granular size=3.5 μ m, inner aperture=100_).The three step linear gradients of using the ACN that is dissolved in 0.1% formic acid under 25 ℃ are with 300 μ L/ minute wash-out pillar.For t=0-0.5 minute, ACN concentration was 9.75% to 24%; For t=0.5-20 minute, ACN concentration was 24% to 90.5%; For t=20-27 minute, ACN concentration was 90.5% to 92.4%.Above-mentioned experiment condition is known as " LC experiment condition " herein.Under the LC experiment condition, the nefrosulfin pyridazone is at 44%ACN place wash-out, and retention time is 6.4 minutes, and stearylamine is at 89%ACN place wash-out, and retention time is 14.5 minutes.Use Agilent MSD 1100 quadruple mass-spectrometers to analyze the sample that passes through the LC fractional separation by ESI-MS, this mass spectrograph is connected in series to LC post (LC/ESI-MS).With the capillary voltage of cation mode and 4000V be matter/lotus than (m/z) be 100 or the ion of 150-1000Da obtain mass-spectrometric data.Every kind of sample is implemented three LC/ESI-MS to be analyzed.Data can be expressed as every kind of ionic m/z (dalton) and retention time (minute) (" m/z, retention time "), wherein the ionic retention time is from the required time of reversed-phase column wash-out in linear ACN gradient.Yet in order to calculate the slight variation of retention time in each experiment, data also can be expressed as m/z and ion from C ₁₈The percentage ratio of ACN during the post wash-out, it represents this ionic inwardness, can not be subjected to testing the remarkably influenced of variability.Relation between percentage ratio ACN when retention time and wash-out can be expressed by following equation:

％ACN＝28.5t+9.75 (0＜t＜0.5)；

％ACN＝3.4103(t-0.5)+24 (0.5＜t＜20)；

％ACN＝0.27143(t-20)+90.5(20＜t＜27)

Yet the value of these parameters should be understood that approximation and may slightly change in experimental period; Yet ion can be discerned reproducedly, and is special when preparing sample with one or more identical interior marks.In the data below, the m/z value is determined to be in ± 0.4m/z in, and when determining the ion wash-out percentage ratio ACN be determined to be in ± 10% in.

1.4. data analysis and result

Analyze hundreds of spectral signatures from every kind of plasma sample.Carry out the comparison of similar features between the spectrum.The selection of alignment algorithm is not crucial for the present invention, and the technician understands that multiple alignment algorithm can be used for this purpose.4930 kinds of spectral signatures have been analyzed altogether.For this embodiment, " feature " used with " peak " exchange corresponding to specific ion.The representative peak of the sample that obtains from 5 Different Individual is displayed in Table 1.First is listed in the percentage ratio of ACN when having listed each ionic m/z and wash-out in the bracket respectively.Remaining row are the corresponding ionic stdn intensity from each patient, and they are by obtaining intensity to two interior target strength criterionizations.Peak more than 400 has the average intensity greater than 0.1.

Table 1

The representative ion that exists among the multiple patient

Ion (m/z, %ACN)	The patient 1	The patient 2	The patient 3	The patient 4	The patient 5
						(293.2，26.8)	43.39	42.44	53.81	45.86	23.24
(496.5，39.0)	37.43	39.88	33.74	36.32	31.81
						(520.5，37.8)	9.067	9.309	7.512	6.086	6.241
(522.5，37.8)	8.568	8.601	7.234	5.520	5.228
						(524.5，42.2)	11.60	12.73	8.941	7.309	6.810
(275.3，32.0)	6.966	7.000	8.911	5.896	5.590
						(544.5，37.8)	3.545	3.915	3.182	2.365	2.342
(393.3，26.4)	1.517	2.092	2.418	2.439	2.498
						(132.3，24.3)	2.317	2.417	3.953	4.786	2.982
(437.4，27.4)	1.769	1.997	2.418	2.706	2.166
						(518.5，39.0)	3.731	3.792	6.758	3.058	2.605
(349.3，25.6)	1.249	1.663	1.910	1.806	1.660
						(203.2，24.1)	3.722	3.485	4.900	3.155	2.342
(481.4，27.7)	1.570	1.259	1.987	2.246	1.612

Can identify ion with several different methods, described ion provides information for the decision rules of distinguishing SIRS and septicopyemia group.In this embodiment, selected method is (1) relatively average ion intensity and (2) use data analysis algorithm generation classification tree between two groups.

1.4.1 compare average ion intensity

Difference between the more outstanding SIRS of average ion intensity and the septicopyemia patient in the individual ionic strength.For septicopyemia group and SIRS group average respectively the standardized ionic strength more than 1800.Average intensity in septicopyemia group or the SIRS group is separated analysis greater than stdn intensity in 0.1 ion and two groups less than 0.1 ion.Determined that the septicopyemia group is to the ratio of stdn intensity in the SIRS group greater than about 400 kinds of ionic average intensity of 0.1.Being distributed among Fig. 3 of these ionic relative intensity ratios shows.

Use this method, observing 23 kinds of ions (listing in the table 2) demonstrates the intensity height at least 3 times (see Fig. 3, wherein the natural logarithm of ionic strength is greater than about 1.1) among the strength ratio SIRS patient in the septicopyemia patient and is present among the half septicopyemia patient at least and is present in usually among about 1/3 or 1/4 the SIRS patient.In this context, the average intensity that " existence " of biomarker refers to this biomarker in the particular patient is at least 25% of all patients' stdn intensity.Although these ions, perhaps its subclass will can be used for implementing method of the present invention, also can use other ion or other ionic subclass.

Table 2

The percentage ratio that contains listed ionic patient sample

Ion #	(m/z[Da], retention time [min])	The %ACN of wash-out	The septicopyemia patient's that ion exists percentage ratio	The SIRS patient's that ion exists percentage ratio
					1	(520.4，5.12)	39.75	94	35
2	(490.3，5.12)	39.75	76	35
					3	(407.2，4.72)	38.39	76	25
4	(564.4，5.28)	40.30	71	35
					5	(608.4，5.39)	40.68	71	30
6	(564.3，2.14)	29.59	71	25
					7	(476.4，4.96)	39.21	65	30
8	(476.3，1.86)	28.64	65	35
					9	(377.2，4.61)	38.02	65	15
10	(547.4，5.28)	40.30	65	20
					11	(657.4，5.53)	41.15	65	30
12	(481.3，4.96)	39.21	59	25
					13	(432.3，4.80)	38.66	59	30
14	(481.2，1.86)	28.64	59	20
					15	(388.3，4.58)	37.91	59	20
16	(363.2，4.40)	37.30	59	20
					17	(261.2，1.26)	26.59	59	40
18	(377.2，9.32)	54.08	59	15
					19	(534.3，5.30)	40.37	59	30
20	(446.3，4.94)	39.14	59	25
					21	(437.2，1.42)	27.13	53	25
22	(451.3，4.94)	39.14	53	15
					23	(652.5，5.51)	41.08	53	20

The subclass of these biomarkers exists with at least 3 times high intensity in the great majority of the positive colony of septicopyemia.Particularly, at least 12 kinds of levels finding these biomarkers in septicopyemia-positive colony more than half raise, and have at least 7 kinds of biomarkers in the positive colony of 85% septicopyemia, the combination that shows these marks will provide the useful predictor of septicopyemia outbreak.Level for all biomarkers of the positive colony of SIRS-all raises, and is as shown in table 3.

Table 3

The septicopyemia group is to the ionic strength in the SIRS group

Ion	The intensity of septicopyemia group	The intensity of SIRS group	Intensity rate: septicopyemia/SIRS
				(437.2，1.42)	4.13	0.77	5.36
(520.4，5.12)	3.65	0.69	5.29
				(476.4，4.96)	3.34	0.78	3.56
(481.3，4.96)	2.42	0.68	3.56
				(564.4，5.28)	2.39	0.43	5.56
(432.3，4.80)	2.29	0.59	3.88
				(476.3，1.86)	2.12	0.52	4.08
(481.2，1.86)	1.88	0.42	4.48
				(388.3，4.58)	1.83	0.51	3.59
(608.4，5.39)	1.41	0.24	5.88
				(363.2，4.40)	1.35	0.27	5.00
(490.3，5.12)	1.27	0.25	5.08
				(261.2，1.26)	1.24	0.24	5.17
(407.2，4.72)	1.05	0.17	6.18
				(377.2，9.32)	1.04	0.27	3.85
(534.3，5.30)	0.88	0.16	5.50
				(446.3，4.94)	0.88	0.22	4.00
(547.4，5.28)	0.86	0.16	5.38
				(451.3，4.94)	0.86	0.17	5.06
(377.2，4.61)	0.84	0.22	3.82
				(564.3，2.14)	0.62	0.14	4.43
(652.5，5.51)	0.62	0.10	6.20
				(657.4，5.53)	0.39	0.11	3.55

Observe two kinds of listed in the table 4 ions high 3 times in the average strength ratio septicopyemia colony of SIRS colony (see Fig. 3, wherein the natural logarithm of ionic strength ratio is less than about-1.1).

Table 4

The septicopyemia group is organized ionic strength to SIRS

Ion	The intensity of septicopyemia group	The intensity of SIRS group	Intensity rate: septicopyemia/SIRS
				(205.0，0.01)	0.26	0.81	0.32
(205.2，3.27)	0.29	0.82	0.35

Identified 32 kinds of average intensity greater than 0.1 ion, height is at least 3 times in the strength ratio SIRS group of these ions in the septicopyemia group.These ions are listed in table 5A.Equally, identified 48 kinds of average intensity less than 0.1 ion, height is at least 3 times in the strength ratio SIRS group of these ions in the septicopyemia group.These ions are listed in table 5B.(negative retention time reflected retention time internally mark this fact of stdn).

Table 5A

The ion of average intensity＞0.1

Ion	The intensity of septicopyemia group	The intensity of SIRS group	Intensity rate: septicopyemia/SIRS	Ln (ratio)
					(365.2，2.69)	1.031828095	0.135995335	7.587231542	2.026467
(305.2，1.87)	3.070957223	0.481494549	6.377968828	1.85285
					(407.2，4.72)	0.913022768	0.166525859	5.482768698	1.70161
(459.1，0.83)	0.58484531	0.106723807	5.479989222	1.701103
					(652.5，5.51)	0.528195058	0.102545088	5.150856731	1.639163
(608.4，5.39)	1.205608851	0.236066662	5.107069514	1.630626
					(415.3，4.80)	2.321268423	0.46651355	4.975779207	1.604582
(319.0，0.69)	1.034850099	0.209420422	4.941495631	1.597668
					(534.3，5.30)	0.756349296	0.158850924	4.761378001	1.560537
(564.4，5.28)	2.037002742	0.432651771	4.708180752	1.549302
					(437.2，1.42)	3.536425702	0.770241153	4.591322718	1.524168
(520.4，5.12)	3.115934457	0.685511116	4.545417838	1.51412
					(261.2，1.26)	1.078475479	0.239640228	4.500394154	1.504165
(363.2，4.40)	1.159043471	0.265797517	4.360625655	1.472616
					(451.3，4.94)	0.738875795	0.170611107	4.330760214	1.465743
(490.3，5.12)	1.084054201	0.25339878	4.278056119	1.453499
					(409.3，2.79)	1.172523824	0.281931606	4.158894565	1.425249
(497.3，4.98)	0.409558491	0.100673382	4.068190437	1.403198
					(453.2，2.97)	0.738638127	0.184100346	4.012149581	1.389327
(481.2，1.86)	1.609705934	0.418739646	3.844168924	1.346557
					(564.3，2.14)	0.531918507	0.139341563	3.817371482	1.339562
(476.4，4.96)	2.847539378	0.784495859	3.629769802	1.289169
					(446.3，4.94)	0.752613738	0.216182996	3.481373426	1.247427
(476.3，1.86)	1.811980008	0.521460142	3.474819762	1.245543
					(377.2，4.61)	0.75347133	0.217838186	3.458857892	1.240938
(344.3，4.21)	0.560262239	0.164687938	3.401962791	1.224353
					(377.2，9.32)	0.902933137	0.267048623	3.381156311	1.218218
(432.3，4.80)	1.957941965	0.588612075	3.326370706	1.201882

(595.4，6.36)	0.41462875	0.125522805	3.303214496	1.194896
					(358.3，4.40)	0.351038883	0.106282278	3.302891964	1.194798
(657.4，5.53)	0.336357992	0.105101129	3.200327108	1.163253
					(388.3，4.58)	1.561368263	0.510848809	3.056419503	1.117244

Table 5B

The ion of average intensity＜0.1

Ion	The intensity of septicopyemia group	The intensity of SIRS group	Intensity rate: septicopyemia/SIRS	Ln (ratio)
					(282.2，0.91)	0.16624	0.00024	693.08684	6.54116
(289.2，6.44)	0.13088	0.00143	91.27187	4.51384
					(821.9，2.49)	0.13670	0.00996	13.72695	2.61936
(385.3，1.24)	0.32177	0.03201	10.05211	2.30778
					(843.9，2.47)	0.11866	0.01206	9.83497	2.28594
(407.2，1.17)	0.75611	0.08227	9.19041	2.21816
					(350.1，0.86)	0.10369	0.01174	8.83532	2.17876
(385.3，4.72)	0.32430	0.03725	8.70689	2.16411
					(399.2，2.99)	0.15303	0.02091	7.31838	1.99039
(152.1，1.51)	0.28888	0.04167	6.93310	1.93631
					(341.0，0.36)	0.26310	0.03828	6.87289	1.92759
(451.2，1.42)	0.45398	0.06645	6.83232	1.92166
					(231.0，-0.41)	0.19637	0.03362	5.84078	1.76486
(534.2，2.20)	0.45796	0.08650	5.29427	1.66663
					(820.5，7.02)	0.12838	0.02439	5.26324	1.66075
(578.4，5.46)	0.45661	0.08861	5.15298	1.63957
					(355.1，2.85)	0.16920	0.03334	5.07491	1.62431
(358.0，2.13)	0.27655	0.05565	4.96946	1.60331
					(696.5，5.65)	0.20458	0.04223	4.84500	1.57795
(622.4，5.61)	0.20034	0.04179	4.79410	1.56739
					(460.3，4.02)	0.18099	0.03950	4.58160	1.52205
(718.0，7.02)	0.11733	0.02564	4.57688	1.52102
					(305.3，6.11)	0.10194	0.02324	4.38703	1.47865

(283.2，1.85)	0.41312	0.09709	4.25497	1.44809
					(701.4，5.63)	0.18369	0.04321	4.25111	1.44718
(541.2，1.71)	0.11482	0.02739	4.19217	1.43322
					(657.3，2.49)	0.17904	0.04280	4.18327	1.43109
(239.2，1.04)	0.10637	0.02553	4.16574	1.42689
					(608.3，2.35)	0.39410	0.09670	4.07556	1.40501
(465.0，1.19)	0.10817	0.02718	3.98030	1.38136
					(333.1，2.00)	0.35105	0.08919	3.93582	1.37012
(497.3，0.88)	0.36172	0.09212	3.92666	1.36779
					(541.3，5.12)	0.13883	0.03559	3.90124	1.36129
(627.3，5.75)	0.16498	0.04259	3.87347	1.35415
					(652.1，5.87)	0.17554	0.04558	3.85130	1.34841
(402.2，1.19)	0.25423	0.06860	3.70596	1.30994
					(553.3，5.38)	0.16633	0.04578	3.63335	1.29016
(635.4，5.53)	0.11925	0.03383	3.52512	1.25992
					(319.2，6.34)	0.17736	0.05035	3.52259	1.25920
(231.1，2.62)	0.20535	0.05906	3.47671	1.24609
					(283.1，4.96)	0.17190	0.04984	3.44919	1.23814
(766.0，6.77)	0.13671	0.04032	3.39069	1.22103
					(358.0，6.00)	0.20857	0.06194	3.36714	1.21406
(179.0，10.16)	0.16841	0.05106	3.29838	1.19343
					(209.1，10.98)	0.13267	0.04090	3.24363	1.17669
(509.3，5.28)	0.26857	0.08291	3.23925	1.17534
					(337.2，9.32)	0.18169	0.05691	3.19236	1.16076
(423.2，2.88)	0.16242	0.05097	3.18669	1.15898

Thereby, reference biomarker spectrum of the present invention can comprise combination of features, wherein these features can be as the m/z about 100 that determines with positive mode by the electron spray(ES) ion massspectrum or the 150Da ionic strength to about 1000Da, and wherein the ratio of these features average intensity in septicopyemia-positive reference colony and SIRS-positive reference colony is about 3: 1 or higher.Alternatively, the ratio of these features average intensity in septicopyemia-positive reference colony and the positive reference of SIRS-colony is about 1: 3 or lower.Because determining that by routine techniques there were these biomarkers in septicopyemia outbreak precontract in 48 hours from biological sample gained biomarker, so expect that these biomarkers are predictors of septicopyemia outbreak.

1.4.2 characteristic strength changes in time

The biomarker checked spectrum demonstrates some features, along with the rising that individuality has to the expression level of these features of development of septicopyemia outbreak, the reduction that has.Expection is peculiar to the physiologic response of infection and/or inflammation in the individuality corresponding to the biomarker of these features.Because top proposition expects that these biomarkers will provide the prediction that is particularly useful for septicopyemia or SIRS state in definite individuality.That is, expection this patient that relatively will determine of these features from the different biological sample gained collection of illustrative plates of body one by one is to serious septicopyemia development or the development of SIRS forward normality.

In listed 23 kinds of ions, 14 kinds demonstrate maximum strength in hour colony of time-48 in table 2, and 8 kinds demonstrate maximum strength in hour colony of time-24, and a kind demonstrates maximum strength in time 0 colony.Change from the intensity of biomarker in the biological sample of septicopyemia group representativeness in time and in Fig. 4 A, to show, and in Fig. 4 B, show from the variation of the intensity of same biomarker in the biological sample of SIRS group.The m/z of this specific ion is 437.2Da, and retention time is 1.42 minutes, and this ion is diagnosing these patients to reach peak value to 48 hours intensity in the septicopyemia group before the conversion of septicopyemia by routine techniques.Thereby the crest of the relative intensity of this ion in biological sample is as the predictor of septicopyemia outbreak in should individuality in about 48 hours.

1.4.3 cross validation

When decision rules was based on the big measure feature of composing from few relatively biomarker, selection bias can influence the evaluation that the feature of information is provided for decision rules.(seeing people such as Ambroise, Proc.Nat ' l Acad.Sci.USA 99:6562-66 (2002)).When data are used to select feature, and selected feature implemented estimated performance with good conditionsi and when not considering variability in the chosen process, selection bias will take place.The result is the estimation that exceeds to classify accuracy.If to selecting skew adjustment, classify accuracy can not reach 100% so, even decision rules also is so (Id.) when being based at random input parameter.Can comprise in the performance estimation process that feature selection avoids selection bias, and no matter this performance estimation process is 10 times of cross validations or a kind of bootstrapping method (seeing that for example, people such as Hastie, as preceding, 7.10-7.11 is merged in this paper as a reference).

In one embodiment of the invention, by 10 times of cross validation detection model performances.Carry out 10 times of cross validations by data being assigned randomly to 10 exclusiveness groups.Then successively with every group of eliminating, and with remaining 9 groups of model-fitting.Group with the model of institute's match is applied to be excluded produces the class probability of being predicted.Can be relatively by producing the prediction classification simply with the class probability of prediction and actual classification membership qualification.For example, if the probability of septicopyemia is that for example, greater than 0.5, the classification of this prediction is a septicopyemia so.

Deviation (Deviance) is that a kind of of comparison probability and actual result measures.Herein, " deviation " is defined as:

Wherein P is the class probability of particular category.When for the classification class probability of reality when high, deviation reduces.Two kinds of models can be to making identical prediction to given data, yet preferred model will have littler prediction deviation.For the iteration each time of 10 iteration in 10 times of cross validations, calculate prediction deviation for the case outside the model-fitting during this iteration.The result is that 10 nothings are wilfully poor.Usually, with the summary of these 10 deviation additions generations to the model performance (that is accuracy) of total data collection.Because when in fact 10 kinds of different models were fit to, cross validation can not prove the performance of particular model.On the contrary, produce 10 kinds of models by common modeling method, and cross validation has proved the performance of this method.The 11st kind of model that obtains from this method will have an estimated performance of 10.Use 10 times of cross validations to cause the performance of model usually less than 100%, but during the biomarker that the sample outside decision rules is applied to the training group obtains, expect that gained performance behind 10 times of cross validations reflects the biologically significant prediction accuracy of this decision rules more accurately.

Classification tree analysis

A kind of method of analyzing these data is to use the classification tree algorithm, pattern and relation in this algorithm research large data sets." classification tree " is to use a series of problems that the recurrence that particular patient is categorized into particular category (for example, septicopyemia or SIRS) is divided, and these problems are designed such that this patient is accurately placed a classification.Whether each problem inquiry patient's condition satisfies given predictor, and each problem is used to the user and descends up to the classification that can determine that this patient enters along classification tree.Herein, " predictor " is that the scope of value of series of features is in this example for having feature m/z and from C among the ACN ₁₈The ionic ionic strength of the elution profile of post." condition " is single, the specific value of detected characteristics in the biomarker spectrum of individuality.In this example, " class name " is septicopyemia and SIRS.Thereby the classification tree user will ask that first kind of ionic strength detecting is whether in the given range of first ionic estimation range in this individual biomarker spectrum.First questions answer will be to be conclusive in SIRS or the septicopyemia at definite this individuality.On the other hand, whether second kind of ionic strength that can also instruct the user to inquire to detect in this individual biomarker spectrum to first questions answer be in the given range of second ionic estimation range.Once more, can determine or instruct the user further finally to be determined up to patient's classification downwards to this second questions answer along classification tree.

With the classification tree Algorithm Analysis representative collection of the 0 o'clock time ionic strength of collecting from septicopyemia and SIRS colony, its result shows in Fig. 5.In this case, the ionic bond of being analyzed comprises that stdn intensity is less than those ions of 0.1.First decision point in the classification tree is that to have m/z be that about 448.5 dalton and the percentage ratio ACN of wash-out place are whether about 32.4% ionic stdn intensity is less than about 0.0414.If this questions answer is a "Yes", continue so along left side branch down to another problem or another class name.In this case, if stdn intensity proceeds to class name " SIRS " and this individuality so and is classified as the SIRS-positive less than about 0.0414, but the septicopyemia feminine gender.If answer is a "No", so along right branch down to another decision point, so up to reaching class name.In this example, be individual prediction class name with three decision points.Although can the patient be categorized as SIRS-or septicopyemia-positive, be to use the extra decision point of other ionic to improve the accuracy of classification usually with single decision point.The technician will understand from large data sets can obtain many different classification trees.That is, for example, many may the combination of biomarker can be used for individual segregation for belonging to SIRS colony or septicopyemia colony.

1.4.5 the multiple regression tree that adds up

The modeling technique that uses a kind of automated flexible classifies as the set of feature and belongs to one of two colonies, and this technology is used multiple regression tree that adds up (MART).The MART model uses the initial offset amount, and this side-play amount is specified the constant that is applied to all predictions, specifies a series of regression tree then.The number of tree of match is specified, is used in the match of this model by the number of commit point in every kind of tree and " the granularity constant " of specifying certain tree how to influence the MART model at all specified.For each iteration, regression tree is by the direction of match with the most precipitous decline of estimation match standard.Take to have the step of the specified length of this granularity constant in this direction.The MART model adds that by initial side-play amount the step that regression tree provides forms like this.Calculate the difference between observed value and the predictor once more, and proceed this circulation, what cause predicting is constantly perfect.This process continues predetermined cycle number or up to causing stopping rule.

Branched number is especially significant fitting parameter in every tree.If each tree only has a branch, this model is only considered a feature and can not be made up two predictors so.If every tree has two branches, this model can hold the interaction of two tunnel between the feature so.Use three trees, this model can hold three the road and interact, or the like.

Use characteristic and known classification state (for example, septicopyemia or SIRS) are determined the value of feature set in the prediction classification state for data set.MART provides personal feature to the contribution of categorised decision rule or measuring of importance.Particularly, in the time of can detecting selection to the single feature of given tree branch this single feature to the percentage contribution of this decision rules with by these features to the importance that determines final decision rules to these feature orderings.Same data set is repeated MART analyze the slightly different ordering that can produce feature, particularly about for setting up more unessential those features of decision rules.The set that can be used for predictability feature of the present invention and their corresponding biomarker can change a little along with those set of this paper proposition.

A module that is implemented in the R statistics programmed environment of MART technology is perhaps found in " bag " (to see people such as Venables, Modern Applied Statistics with S, the 4th edition (Springer, 2002); Www.r-project.org).Use R version 1.7.0 and 1.7.1 to calculate the result of the report in this document.The module (Greg Ridgeway writes) that realizes MART is called as " gbm " and can free download (seeing www.r-project.org).This MART algorithm is modified to be suitable for ten times of cross validations.Grain size parameter is set to 0.05, and 20% data set is ignored at the iteration place that the inside stopping rule of gbm bag is based on each mark.The degree of iteration is set as 1, does not therefore consider the interaction between these features.Gbm wraps the relative importance of estimating each feature based on percentage ratio, and for all features of biomarker, the accumulation of relative importance equals 100%.Have that the feature of high importance accounts at least 90% of total importance, this has the feature of high importance and is reported as and may has predictor.Notice that stopping rule is that model-fitting and feature selection have been contributed a component at random in each MART model of match.Therefore, can select based on a plurality of MART modelings operations of identical data operation slightly different, perhaps may diverse characteristic set.Identical information of forecasting is passed in these different set; Therefore, all set all can be used for the present invention.Expection will produce all possible set of the predicted characteristics in the biomarker spectrum for the enough number of times of MART model-fitting.Therefore, the set of disclosed predictor is only represented and be can be used for the set of individual segregation to those features of colony.

1.3.4 logistic regression analysis

The logistic regression analysis provides the another kind of method of the data stream of analyzing from above-mentioned LC/MS.Height detection " peak intensity " by the peak that in the spectrum of given m/z position, occurs.Lack the peak causes distributing " 0 " to this peak intensity in given m/z position.Obtain the standard deviation (SD) of the peak intensity of given m/z position then from the spectrum of the SIRS that merges and septicopyemia colony.If peak intensity does not change (being SD=0) between SIRS and the septicopyemia colony, do not further consider peak intensity so.Before regression analysis, use the method detected peaks intensity of knowing in this area.Detection algorithm, is described in 11 chapters as preceding usually people such as Hastie.

This feature selection approach has been identified 26 input parameters (that is, biomarker) from time 0 biomarker spectrum, and they are listed in table 6.Although input parameter is arranged with statistics importance, but still can prove that more low-level input parameter remains clinical value and can be used for the present invention. in addition, the technician will understand, if reference colony changes by any way, the importance of the arrangement of so given input parameter can change.

Table 6

The input parameter of time 0 sample

The input parameter importance ranking	m/z (Da)	The %ACN of wash-out	The input parameter importance ranking	m/z (Da)	The %ACN of wash-out
						1	883.6	44.84	14	377.0	25.26
2	718.1	44.94	15	194.1	27.07
						3	957.3	44.84	16	413.4	92.04
4	676.1	44.84	17	651.5	59.98
						5	766.0	44.77	18	114.2	34.40
6	416.3	40.10	19	607.5	45.21
						7	429.4	75.80	20	282.3	37.30
8	820.6	44.84	21	156.2	39.99
						9	399.4	90.43	22	127.3	64.68
10	244.2	26.59	23	687.9	41.84
						11	593.5	43.51	24	439.5	43.34
12	300.4	59.54	25	462.4	72.70
						13	285.3	25.88	26	450.4	64.79

Use this identical logistic regression analysis, can arrange biomarker according to the intraictal importance of the sample prediction septicopyemia that uses hour collection in time-48.This feature selection approach is that time-48 a hour sample has produced 37 input parameters, and is as shown in table 7.

Table 7

Input parameter from time-48 hour sample

The input parameter importance ranking	m/z (Da)	The %ACN of wash-out	The input parameter importance ranking	m/z (Da)	The %ACN of wash-out
						1	162.2	28.57	20	379.3	38.63
2	716.2	46.41	21	423.3	39.04
						3	980	54.52	22	463.4	87.50
4	136.2	24.65	23	965.3	54.15
						5	908.9	57.83	24	265.3	40.10
6	150.2	25.13	25	287.2	40.47
						7	948.7	52.54	26	429.4	83.13
8	298.4	25.52	27	886.9	54.42
						9	293.3	30.45	28	152.2	28.33
10	188.2	30.65	29	431.4	61.34
						11	772.7	47.53	30	335.4	30.72
12	327.4	100.60	31	239.2	43.75
						13	524.5	90.30	32	373.4	61.10
14	205.2	33.28	33	771	24.03
						15	419.4	87.81	34	555.4	41.43
16	804.8	54.86	35	116.2	24.95
						17	496.5	79.18	36	887.2	54.62
18	273.1	29.39	37	511.4	40.95
						19	355.4	95.51

1.4.7Wilcoxon signed rank test analysis

In another method, can identify the single target biomarker with nonparameter test such as the signed rank test of Wilcoxon.Feature in the biomarker spectrum is assigned with " p value ", and it represents that it is the determinacy degree of specific reference colony that biomarker can be used for individual segregation.Usually, the p value with predictive value is lower than about 0.05.Biomarker with low p value can self be used for the classification individuality.Alternatively, it is individual that the combination of two or more biomarkers can be used for classification, wherein selects combination based on the relative p-value of biomarker.Usually, for the given combination of biomarker, preferably have those biomarkers of lower p-value.Also can be by this way with at least 3,4,5,6,10,20,30 or the combination of more kinds of biomarkers to individual segregation.The technician will understand that the relative p value of arbitrary given biomarker can become according to the size of reference colony.

Use the signed rank test of Wilcoxon, to the characteristic allocation p value of the biomarker spectrum that obtains from the biological sample of hour gathering in time 0, time-24 hour and time-48.These p values are listed in table 8,9 and 10 respectively.

Table 8

The p value of time 0 sample

Ion number	M/z (Da), retention time (min)	The p value
			1	(179.0，10.16)	7.701965e-05
2	(512.4，10.44)	1.112196e-04
			3	(371.3，4.58)	2.957102e-04
4	(592.4，15.69)	3.790754e-04
			5	(363.2，4.40)	4.630887e-04
6	(679.4，5.92)	1.261515e-03
			7	(835.0，7.09)	1.358581e-03
8	(377.2，4.61)	1.641317e-03
			9	(490.3，5.12)	1.959479e-03
10	(265.2，4.72)	3.138371e-03
			11	(627.3，5.75)	3.438053e-03
12	(266.7，14.83)	3.470672e-03
			13	(774.9，7.39)	3.470672e-03
14	(142.2，3.38)	4.410735e-03
			15	(142.0，-0.44)	4.443662e-03
16	(231.0，-0.41)	5.080720e-03
			17	(451.3，4.94)	5.096689e-03
18	(753.8，9.34)	5.097550e-03
			19	(399.2，2.99)	5.217724e-03
20	(534.4，10.53)	5.877221e-03
			21	(978.8，6.72)	6.448607e-03
22	(539.3，5.30)	6.651592e-03
			23	(492.2，1.36)	6.697313e-03
24	(730.4，6.54)	6.724428e-03

25	(842.6，10.11)	6.724428e-03
			26	(622.4，5.61)	7.249023e-03
27	(331.7，19.61)	8.137318e-03
			28	(564.3，14.16)	8.419814e-03
29	(415.3，4.80)	8.475773e-03
			30	(229.2，2.39)	8.604155e-03
31	(118.2，5.26)	8.664167e-03
			32	(410.7，0.77)	8.664167e-03
33	(733.5，4.55)	9.271924e-03
			34	(503.3，5.12)	9.413344e-03
35	(453.2，2.97)	9.802539e-03
			36	(534.3，5.30)	1.089928e-02
37	(459.3，4.96)	1.100198e-02
			38	(337.8，5.51)	1.136183e-02
39	(525.4，15.11)	1.136183e-02
			40	(495.3，18.52)	1.282615e-02
41	(763.4，19.81)	1.282615e-02
			42	(256.2，6.03)	1.286693e-02
43	(319.1，15.67)	1.286693e-02
			44	(548.3，5.24)	1.286693e-02
45	(858.8，7.79)	1.287945e-02
			46	(671.4，5.77)	1.310484e-02
47	(353.2，7.38)	1.323194e-02
			48	(844.1，9.68)	1.333814e-02
49	(421.2，4.89)	1.365072e-02
			50	(506.4，19.65)	1.438363e-02
51	(393.3，4.58)	1.459411e-02
			52	(473.3，5.12)	1.518887e-02
53	(189.1，2.87)	1.602381e-02
			54	(528.1，16.18)	1.603446e-02
55	(137.2，9.60)	1.706970e-02
			56	(163.1，10.98)	1.706970e-02
57	(176.1，10.29)	1.706970e-02
			58	(179.1，6.23)	1.706970e-02
59	(271.5，5.01)	1.706970e-02
			60	(272.2，6.49)	1.706970e-02
61	(399.3，27.26)	1.706970e-02
			62	(467.5，5.95)	1.706970e-02
63	(478.0，2.36)	1.706970e-02
			64	(481.3，26.85)	1.706970e-02
65	(931.9，6.72)	1.706970e-02
			66	(970.5，7.00)	1.706970e-02

67	(763.2，16.60)	1.730862e-02
			68	(544.4，15.56)	1.732997e-02
69	(666.4，5.77)	1.750379e-02
			70	(337.2，9.32)	1.812839e-02
71	(407.2，1.17)	1.852695e-02
			72	(597.2，5.32)	1.895944e-02
73	(333.1，2.00)	1.930165e-02
			74	(490.3，13.78)	1.989224e-02
75	(139.1，16.05)	2.026959e-02
			76	(991.7，16.60)	2.046716e-02
77	(814.2，6.66)	2.121091e-02
			78	(665.4，15.46)	2.127247e-02
79	(875.9，10.08)	2.127247e-02
			80	(144.0，0.25)	2.137456e-02
81	(622.7，4.14)	2.178625e-02
			82	(377.2，12.32)	2.240973e-02
83	(509.3，5.28)	2.243384e-02
			84	(349.2，2.69)	2.252208e-02
85	(302.0，19.54)	2.266635e-02
			86	(411.0，2.20)	2.303751e-02
87	(296.2，16.48)	2.373348e-02
			88	(299.6，15.62)	2.440816e-02
89	(162.1，0.49)	2.441678e-02
			90	(372.0，0.62)	2.472854e-02
91	(377.2，9.32)	2.514306e-02
			92	(979.6，10.14)	2.530689e-02
93	(417.3，15.61)	2.550843e-02
			94	(281.7，19.54)	2.563580e-02
95	(276.2，5.27)	2.598704e-02
			96	(229.2，-0.79)	2.626971e-02
97	(346.1，7.46)	2.654063e-02
			98	(356.2，9.88)	2.654063e-02
99	(616.4，8.05)	2.683578e-02
			100	(850.4，7.65)	2.697931e-02
101	(495.3，5.12)	2.712924e-02
			102	(446.3，4.94)	2.739049e-02
103	(476.3，1.86)	2.770535e-02
			104	(520.4，5.12)	2.774232e-02
105	(428.3，6.20)	2.808469e-02
			106	(536.3，17.97)	2.863714e-02
107	(860.3，6.94)	2.894386e-02
			108	(762.9，16.65)	2.958886e-02

109	(788.9，6.43)	2.967800e-02
			110	(970.1，6.47)	2.967800e-02
111	(853.8，5.77)	3.039550e-02
			112	(913.6，9.50)	3.039550e-02
113	(407.2，4.72)	3.041346e-02
			114	(335.2，16.10)	3.047982e-02
115	(331.2，12.93)	3.075216e-02
			116	(512.3，13.80)	3.075216e-02
117	(895.8，6.80)	3.084773e-02
			118	(120.2，8.37)	3.110972e-02
119	(238.2，9.32)	3.110972e-02
			120	(506.3，8.10)	3.110972e-02
121	(949.9，6.66)	3.115272e-02
			122	(176.1，6.96)	3.161957e-02
123	(664.9，2.41)	3.275550e-02
			124	(551.4，18.56)	3.290912e-02
125	(459.0，5.98)	3.389516e-02
			126	(811.5，7.73)	3.389516e-02
127	(919.9，10.01)	3.414450e-02
			128	(547.4，5.28)	3.444290e-02
129	(895.4，6.62)	3.460947e-02
			130	(132.2，0.79)	3.549773e-02
131	(944.8，9.65)	3.567313e-02
			132	(730.7，6.46)	3.581882e-02
133	(529.5，16.70)	3.666990e-02
			134	(449.3，24.40)	3.687266e-02
135	(465.3，5.08)	3.725633e-02
			136	(481.3，4.96)	3.956117e-02
137	(250.1，14.23)	3.982131e-02
			138	(565.3，16.05)	3.982131e-02
139	(559.0，15.30)	3.994530e-02
			140	(555.3，4.18)	4.078620e-02
141	(568.4，15.49)	4.118355e-02
			142	(120.0，11.52)	4.145499e-02
143	(120.2，14.91)	4.145499e-02
			144	(167.0，5.00)	4.145499e-02
145	(173.0，19.96)	4.145499e-02
			146	(324.9，2.27)	4.145499e-02
147	(328.8，19.98)	4.145499e-02
			148	(345.7，16.95)	4.145499e-02
149	(407.2，12.07)	4.145499e-02
			150	(478.3，3.69)	4.145499e-02

151	(484.2，8.40)	4.145499e-02
			152	(502.2，4.55)	4.145499e-02
153	(597.4，11.40)	4.145499e-02
			154	(612.3，6.40)	4.145499e-02
155	(700.3，9.40)	4.145499e-02
			156	(730.5，11.63)	4.145499e-02
157	(771.4，6.02)	4.145499e-02
			158	(811.9，10.99)	4.145499e-02
159	(859.9，2.47)	4.145499e-02
			160	(450.3，11.99)	4.145499e-02
161	(619.3，11.42)	4.165835e-02
			162	(102.1，6.16)	4.238028e-02
163	(717.5，9.11)	4.238028e-02
			164	(606.0，7.63)	4.317929e-02
165	(627.2，2.48)	4.317929e-02
			166	(252.1，6.62)	4.318649e-02
167	(657.4，5.53)	4.332436e-02
			168	(635.7，7.94)	4.399442e-02
169	(167.2，14.42)	4.452609e-02
			170	(812.5，10.24)	4.528236e-02
171	(575.4，10.00)	4.533566e-02
			172	(379.3，15.55)	4.644328e-02
173	(468.3，13.44)	4.644328e-02
			174	(295.3，16.10)	4.721618e-02
175	(715.8，7.68)	4.736932e-02
			176	(810.6，19.21)	4.759452e-02
177	(159.1，13.02)	4.795773e-02
			178	(435.2，0.83)	4.795773e-02
179	(443.0，11.99)	4.795773e-02
			180	(468.4，19.65)	4.795773e-02
181	(909.8，9.52)	4.795773e-02
			182	(647.2，2.45)	4.838671e-02
183	(564.4，5.28)	4.958429e-02

Table 9

The p value of times 24 sample

Ion number	M/z (Da), retention time (min)	The p value
			1	(265.2，4.72)	0.0003368072
2	(785.5，9.30)	0.0006770673
			3	(685.1，6.85)	0.0010222902
4	(608.4，5.39)	0.0014633974
			5	(141.1，5.13)	0.0018265874
6	(652.5，5.51)	0.0022097623
			7	(228.0，3.12)	0.0029411592
8	(660.1，3.90)	0.0032802432
			9	(235.1，4.04)	0.0038917632
10	(287.1，4.72)	0.0045802571
			11	(141.2，1.46)	0.0049063026
12	(553.3，5.38)	0.0053961549
			13	(114.2，2.49)	0.0060009121
14	(490.3，5.12)	0.0064288387
			15	(142.0，-0.44)	0.0064784467
16	(428.3，6.20)	0.0064784467
			17	(564.4，5.28)	0.0081876219
18	(678.8，2.37)	0.0089256763
			19	(155.1，2.87)	0.0091072246
20	(377.2，4.61)	0.0098626515
			21	(221.0，1.92)	0.0102589726
22	(463.2，1.88)	0.0102589726
			23	(142.2，3.38)	0.0106568532
24	(231.0，-0.41)	0.0106568532
			25	(256.2，6.03)	0.0106568532
26	(597.2，2.05)	0.0106568532
			27	(638.8，2.35)	0.0112041041
28	(800.6，1.53)	0.0112041041
			29	(385.3，24.07)	0.0113535538
30	(578.4，5.46)	0.0114707005
			31	(352.3，11.76)	0.0115864528
32	(858.2，10.41)	0.0115864528
			33	(889.7，16.16)	0.0115864528
34	(190.1，3.99)	0.0120870451
			35	(493.3，26.36)	0.0120870451
36	(608.3，2.35)	0.0122930750
			37	(958.8，6.36)	0.0127655270
38	(235.0，0.51)	0.0128665507
			39	(739.5，9.45)	0.0139994021
40	(525.2，1.92)	0.0141261152
			41	(372.4，11.66)	0.0148592431
42	(415.3，4.80)	0.0154439839

43	(439.2，9.40)	0.0154583510
			44	(819.0，2.11)	0.0156979793
45	(459.3，20.83)	0.0161386158
			46	(372.2，5.10)	0.0169489151
47	(875.4，19.37)	0.0170124705
			48	(989.2，10.14)	0.0184799654
49	(179.0，10.16)	0.0190685234
			50	(231.0，6.41)	0.0191486950
51	(460.9，1.77)	0.0194721634
			52	(813.5，9.83)	0.0194721634
53	(274.2，4.67)	0.0194863889
			54	(158.2，10.93)	0.0203661514
55	(676.7，1.07)	0.0208642732
			56	(171.2，25.87)	0.0213201435
57	(520.4，5.12)	0.0214439678
			58	(523.3，22.32)	0.0216203784
59	(329.0，1.27)	0.0222231947
			60	(585.2，15.27)	0.0222231947
61	(534.3，5.30)	0.0224713144
			62	(349.2，2.69)	0.0234305681
63	(263.2，5.05)	0.0240107773
			64	(278.1，5.24)	0.0240107773
65	(425.9，6.20)	0.0240107773
			66	(575.4，10.00)	0.0240107773
67	(649.3，5.75)	0.0240107773
			68	(152.1，1.51)	0.0244163058
69	(785.1，9.29)	0.0244163058
			70	(509.3，5.28)	0.0257388421
71	(525.4，15.11)	0.0259747750
			72	(261.2，21.02)	0.0259960666
73	(914.1，10.04)	0.0260109531
			74	(465.3，5.08)	0.0260926970
75	(433.3，18.18)	0.0271021410
			76	(300.0，21.90)	0.0275140464
77	(811.6，19.44)	0.0276109304
			78	(710.5，5.90)	0.0295828987
79	(569.2，2.00)	0.0302737381
			80	(388.3，4.58)	0.0308414401
81	(173.1，6.52)	0.0308972074
			82	(266.7，14.83)	0.0308972074
83	(286.2，12.60)	0.0308972074
			84	(619.3，19.04)	0.0308972074
85	(682.6，9.44)	0.0308972074
			86	(717.3，17.96)	0.0308972074
87	(920.6，10.61)	0.0308972074
			88	(988.4，10.46)	0.0308972074
89	(271.1，15.08)	0.0313675727
			90	(740.5，6.02)	0.0316777607

91	(839.6，20.85)	0.0316777607
			92	(610.9，2.44)	0.0329765016
93	(179.1，13.20)	0.0330555292
			94	(701.4，5.63)	0.0330555292
95	(175.1，8.49)	0.0332024906
			96	(279.0，2.32)	0.0337986949
97	(670.4，9.09)	0.0337986949
			98	(415.3，15.42)	0.0338750641
99	(183.1，6.88)	0.0343045905
			100	(160.1，0.50)	0.0344826274
101	(459.3，4.96)	0.0352364197
			102	(305.2，1.87)	0.0353424937
103	(216.2，4.54)	0.0363303150
			104	(603.3，6.48)	0.0363303150
105	(914.1，6.94)	0.0368261384
			106	(205.1，6.75)	0.0368844784
107	(446.3，4.94)	0.0371476565
			108	(513.1，4.48)	0.0380144912
109	(676.0，6.65)	0.0382429645
			110	(366.1，0.86)	0.0383351335
111	(227.9，-0.44)	0.0386073936
			112	(641.4，7.27)	0.0387953825
113	(395.2，24.02)	0.0388820140
			114	(929.6，7.27)	0.0389610390
115	(371.3，4.58)	0.0392271166
			116	(402.2，1.19)	0.0392271166
117	(127.0，4.75)	0.0397364228
			118	(193.0，1.36)	0.0404560651
119	(194.0，1.00)	0.0404560651
			120	(379.3，15.55)	0.0404560651
121	(495.3，12.82)	0.0404560651
			122	(823.4，9.50)	0.0404560651
123	(235.1，8.53)	0.0405335640
			124	(476.4，4.96)	0.0421855472
125	(472.5，11.18)	0.0425955352
			126	(693.1，5.95)	0.0426922311
127	(274.1，7.80)	0.0428211411
			128	(402.2，12.86)	0.0428660082
129	(746.8，2.42)	0.0429101967
			130	(801.0，2.11)	0.0429101967
131	(366.7，5.89)	0.0434178862
			132	(458.4，4.70)	0.0434178862
133	(369.4，26.36)	0.0440035652
			134	(601.0，0.43)	0.0440035652
135	(249.2，6.55)	0.0440434139
			136	(666.4，5.77)	0.0444571249
137	(415.4，12.38)	0.0447164378
			138	(652.1，5.87)	0.0447164378

139	(472.2，11.12)	0.0453906033
			140	(441.4，24.91)	0.0464361698
141	(575.4，20.88)	0.0464361698
			142	(393.3，4.58)	0.0464768588
143	(620.7，0.74)	0.0465716607
			144	(842.9，6.93)	0.0465716607
145	(685.4，17.53)	0.0468826130
			146	(476.3，1.86)	0.0472378721
147	(399.2，2.99)	0.0479645296
			148	(211.1，13.48)	0.0488051357
149	(357.3，9.11)	0.0488051357
			150	(313.2，17.63)	0.0495881957

Table 10

The p value of times 48 sample

Ion number	M/z (Da), retention time (min)	The p value
			1	(845.2，6.33)	0.001343793
2	(715.8，7.68)	0.002669885
			3	(745.7，6.03)	0.002743002
4	(802.4，8.16)	0.002822379
			5	(648.5，-0.24)	0.003721455
6	(745.3，6.02)	0.005142191
			7	(608.4，5.39)	0.005491954
8	(265.2，4.72)	0.006272684
			9	(505.3，12.78)	0.006518681
10	(371.3，4.58)	0.006931949
			11	(261.2，1.26)	0.008001346
12	(971.4，10.51)	0.008726088
			13	(152.1，1.51)	0.009174244
14	(685.1，6.85)	0.009704974
			15	(456.4，9.80)	0.010451432
16	(214.2，15.68)	0.010792220
			17	(446.0，2.54)	0.010792220
18	(346.1，7.46)	0.011152489
			19	(227.0，23.11)	0.011834116
20	(407.2，1.17)	0.011946593
			21	(435.3，19.92)	0.011946593
22	(451.3，4.94)	0.012261329
			23	(274.1，7.80)	0.012266073
24	(869.0，9.70)	0.012303709
			25	(274.2，4.67)	0.012859736
26	(789.4，6.11)	0.012890139
			27	(576.4，3.29)	0.013087923
28	(930.0，9.75)	0.013087923

29	(512.4，10.44)	0.014315178
			30	(878.9，7.28)	0.014513409
31	(503.3，5.12)	0.015193810
			32	(180.1，4.54)	0.015226001
33	(209.1，5.03)	0.015254389
			34	(616.2，11.90)	0.016782325
35	(443.3，3.41)	0.017490379
			36	(572.6，4.30)	0.017654283
37	(931.9，6.72)	0.018138469
			38	(966.4，10.49)	0.019031437
39	(541.3，5.12)	0.019316716
			40	(470.3，10.72)	0.019821985
41	(281.3，16.88)	0.020436455
			42	(407.2，4.72)	0.021104001
43	(627.2，2.48)	0.021491454
			44	(313.2，6.31)	0.022912878
45	(173.2，15.68)	0.023189016
			46	(675.6，5.75)	0.023820433
47	(137.2，9.60)	0.023895386
			48	(357.2，5.65)	0.023895386
49	(372.0，0.62)	0.023895386
			50	(635.3，2.38)	0.023895386
51	(743.8，4.55)	0.023895386
			52	(185.2，6.29)	0.024742907
53	(930.4，7.60)	0.024770578
			54	(564.4，5.28)	0.024811749
55	(415.2，9.09)	0.025574438
			56	(697.3，16.10)	0.025714289
57	(657.3，2.49)	0.025825394
			58	(996.1，9.94)	0.026026402
59	(185.0，0.10)	0.027530406
			60	(333.1，2.00)	0.027840095
61	(611.3，6.59)	0.028096875
			62	(283.3，18.53)	0.028392609
63	(506.3，8.10)	0.028392609
			64	(726.4，5.67)	0.028392609
65	(397.3，20.91)	0.029361285
			66	(311.9，2.10)	0.029433328
67	(473.3，8.15)	0.029433328
			68	(490.2，8.85)	0.029433328
69	(493.3，22.99)	0.029433328
			70	(577.2，3.56)	0.029433328
71	(653.7，6.16)	0.029433328
			72	(757.5，16.28)	0.029433328
73	(819.0，2.11)	0.029433328
			74	(853.5，13.13)	0.029433328
75	(889.2，6.42)	0.029433328
			76	(929.6，10.60)	0.029433328

77	(963.3，9.70)	0.029433328
			78	(982.1，9.39)	0.029433328
79	(446.3，4.94)	0.030176399
			80	(959.5，10.86)	0.030176399
81	(169.1，5.03)	0.030177290
			82	(906.7，9.75)	0.030212739
83	(772.1，7.79)	0.030482971
			84	(857.0，9.70)	0.030966151
85	(861.8，9.74)	0.030966151
			86	(377.2，12.32)	0.031285164
87	(229.2，-0.79)	0.031539774
			88	(229.2，2.39)	0.031539774
89	(740.4，9.58)	0.031759640
			90	(958.3，9.66)	0.031759640
91	(739.5，18.01)	0.032714845
			92	(377.2，4.61)	0.032818612
93	(144.0，0.25)	0.032941894
			94	(459.3，4.96)	0.033735985
95	(715.8，4.37)	0.034116302
			96	(649.0，2.13)	0.034332004
97	(776.3，6.78)	0.034520017
			98	(827.1，9.58)	0.034662245
99	(439.2，9.40)	0.035385909
			100	(376.0，2.11)	0.038036916
101	(734.6，7.21)	0.038036916
			102	(402.2，1.19)	0.038177664
103	(740.5，6.02)	0.038356830
			104	(502.5，4.01)	0.038481929
105	(694.4，6.02)	0.039047025
			106	(331.0，0.74)	0.039943461
107	(302.1，4.44)	0.040965049
			108	(836.1，8.31)	0.041276236
109	(909.4，9.75)	0.041642229
			110	(358.0，2.13)	0.041676687
111	(502.2，4.55)	0.042049098
			112	(302.2，0.79)	0.042062826
113	(936.9，9.51)	0.042143408
			114	(492.2，1.36)	0.042286848
115	(204.2，5.03)	0.043172669
			116	(701.4，5.63)	0.044132315
117	(373.3，24.05)	0.045041891
			118	(657.4，5.53)	0.045102516
119	(357.3，15.86)	0.045170280
			120	(670.9，6.71)	0.045249625
121	(850.0，7.56)	0.046346695
			122	(576.4，16.02)	0.046573286
123	(670.4，9.09)	0.046609659
			124	(578.4，5.46)	0.047297957

125	(525.3，5.12)	0.047503607
			126	(926.0，6.12)	0.047503607
127	(987.3，9.56)	0.047882538
			128	(231.0，-0.41)	0.048437237
129	(608.3，2.35)	0.048607203
			130	(966.7，10.60)	0.048825822

Alternatively, nonparameter test (for example, the signed rank test of Wilcoxon) can be used for based on the gradual appearance of feature in the colony of forward septicopyemia development or disappears finding the p value of feature.In this check form, at first detect the baseline value of given feature, the data when this detection uses septicopyemia and SIRS group to enter research (day 1 sample).Then with characteristic strength in septicopyemia and the SIRS sample with for example, the characteristic strength comparison in-48 hours samples is to determine whether this characteristic strength increases or reduced from its baseline value.At last, the p value is distributed to the different of characteristic strength and baseline in septicopyemia colony and the SIRS colony.Do not show listed p value among the 11-13 below in detecting p value, not obtained simultaneously with these of baseline.

Table 11

The p value of the feature different: time 0 sample with baseline

Ion number	M/z (Da), retention time (min)	The p value
			1	(991.7，16.6)	0.000225214
2	(592.4，15.69)	0.001008201
			3	(733.5，4.55)	0.001363728
4	(173.1，23.44)	0.001696095
			5	(763.2，16.6)	0.001851633
6	(932.2，6.72)	0.002380877
			7	(842.6，10.11)	0.002575890
8	(295.9，15.78)	0.002799236
			9	(512.4，10.44)	0.004198319
10	(551.4，24.89)	0.005132229
			11	(167.1，10.99)	0.005168091
12	(857.8，8.21)	0.005209485
			13	(763.4，19.81)	0.005541078
14	(931.9，6.72)	0.006142506
			15	(167.2，14.42)	0.006349154
16	(510.4，17.91)	0.006427070
			17	(295.3，16.1)	0.007165849
18	(353.2，7.38)	0.007255100

19	(653，6.71)	0.007848203
			20	(730.4，6.54)	0.008402925
21	(142，0.44)	0.008578959
			22	(331.7，19.61)	0.008807931
23	(386.3，9.47)	0.009227968
			24	(524.4，19.33)	0.010256841
25	(741.5，23.22)	0.010329009
			26	(272.2，6.49)	0.010345274
27	(448.3，9.24)	0.010666648
			28	(713.5，21.99)	0.011150954
29	(353.3，22.38)	0.011224096
			30	(457.2，0.88)	0.011653586
31	(708.9，0.37)	0.012197946
			32	(256.2，6.03)	0.013251532
33	(721.4，23.49)	0.014040014
			34	(496.4，16.6)	0.014612622
35	(634.9，27.04)	0.015093015
			36	(663.3，2.06)	0.015093015
37	(679.4，5.92)	0.015176669
			38	(521.4，23.84)	0.015526731
39	(358.3，4.4)	0.015795031
			40	(409.2，6.95)	0.015875221
41	(537.3，23)	0.016202704
			42	(875.4，19.37)	0.016372468
43	(875.9，10.08)	0.016391836
			44	(265.2，9.37)	0.016924737
45	(450.3，11.99)	0.017293769
			46	(329，1.27)	0.017732659
47	(534.4，10.53)	0.018580510
			48	(616.2，11.9)	0.018703298
49	(177，0.93)	0.018855039
			50	(772.1，16.51)	0.018991142
51	(424.2，6.12)	0.019195215
			52	(277.3，21.72)	0.020633230
53	(333.2，7.39)	0.020898404
			54	(742.8，4.02)	0.021093249
55	(428.3，6.2)	0.021697014
			56	(946，10.49)	0.021935440
57	(970.5，7)	0.021999796
			58	(281.7，19.54)	0.022055564
59	(568.4，15.49)	0.022208535
			60	(700.3，9.4)	0.022500138
61	(118.2，5.26)	0.022773904
			62	(601.3，5.46)	0.023578505
63	(818.3，7.18)	0.023788872
			64	(799.4，9.64)	0.023906673
65	(244.1，2.22)	0.024125162
			66	(145.1，3.99)	0.024385288

67	(328.8，19.98)	0.024385288
			68	(342.4，13.41)	0.025034251
69	(356.2，5.6)	0.025034251
			70	(321.3，19.96)	0.025128604
71	(523.3，13.8)	0.025164665
			72	(504.3，15.49)	0.025894254
73	(842.3，10.76)	0.026070176
			74	(585.3，25.35)	0.026196933
75	(176.1，10.29)	0.027193290
			76	(399.3，27.26)	0.027193290
77	(761.8，7.89)	0.027193290
			78	(909.8，9.52)	0.027193290
79	(291.2，12.57)	0.029135281
			80	(715.8，7.68)	0.030440991
81	(546.4，19.33)	0.030479818
			82	(795.5，20.72)	0.030479818
83	(321，19.53)	0.030693238
			84	(746.8，10.2)	0.030888031
85	(831.5，20.87)	0.030888031
			86	(872.9，11.6)	0.030888031
87	(598，8.58)	0.031026286
			88	(407.2，12.07)	0.031941032
89	(645.3，13.42)	0.031941032
			90	(662.1，8.16)	0.031941032
91	(179，10.16)	0.032126841
			92	(779.5，19.79)	0.032301988
93	(171.2，25.87)	0.032868402
			94	(979.6，10.14)	0.033098647
95	(245.2，22.24)	0.033117202
			96	(370.3，2.3)	0.033696034
97	(433.3，5.29)	0.033696034
			98	(771.4，10.01)	0.033696034
99	(876.3，9.94)	0.033696034
			100	(893，7.09)	0.033919037
101	(669.2，2.13)	0.034234876
			102	(643.3，5.67)	0.034557232
103	(991.3，9.72)	0.035680492
			104	(577.5，16.48)	0.036136938
105	(820，6.38)	0.036179853
			106	(856.6，10.29)	0.036179853
107	(453.2，6.62)	0.036689053
			108	(652.1，5.87)	0.037082670
109	(944.8，9.65)	0.037337126
			110	(494.4，14.75)	0.037526457
111	(185，11.17)	0.037568360
			112	(229.2，0.79)	0.037574432
113	(245.1，11.44)	0.038031041
			114	(279.3，20.72)	0.038253242

115	(781.5，20.04)	0.038253242
			116	(409.4，22.56)	0.038673618
117	(315.2，14.29)	0.039895232
			118	(759.5，9.33)	0.040499878
119	(995.1，9.94)	0.040516802
			120	(848.3，9.66)	0.040554157
121	(263.3，22.26)	0.041183545
			122	(267.7，16.55)	0.041183545
123	(544.4，15.56)	0.041183545
			124	(617.5，17.71)	0.041406719
125	(411.5，1.06)	0.041454989
			126	(597.4，11.4)	0.041454989
127	(771.4，6.02)	0.041454989
			128	(901.9，1.03)	0.041454989
129	(415.2，9.09)	0.041542794
			130	(430.3，9.1)	0.041922297
131	(414.3，4.29)	0.043298568
			132	(414.9，5.86)	0.043427801
133	(444.2，6)	0.043665836
			134	(505.3，12.78)	0.043665836
135	(231，0.41)	0.043722631
			136	(370.3，10.79)	0.044296546
137	(653.5，19.99)	0.044296546
			138	(291.7，15.37)	0.044815129
139	(531.3，21.48)	0.044870846
			140	(715.4，5.89)	0.044985107
141	(327.3，16.98)	0.045218533
			142	(499.4，15.11)	0.046077647
143	(766.2，15.77)	0.046332971
			144	(664.2，11.84)	0.047191074
145	(567.4，20.79)	0.047549465
			146	(809.6，21.33)	0.047600425
147	(393.3，21.08)	0.048014243
			148	(754.6，7.21)	0.048520560
149	(298.3，24.36)	0.049732041
			150	(883.3，6.69)	0.049768492
151	(468.3，13.44)	0.049813626
			152	(665.4，15.46)	0.049918030

Table 12

The p value of the feature different: time-24 hour sample with baseline

Ion number	M/z (Da), retention time (min)	The p value
			1	(875.4，19.37)	0.0006856941
2	(256.2，6.03)	0.0009911606
			3	(228，3.12)	0.0014153532
4	(227.9，0.44)	0.0015547019
			5	(879.8，4.42)	0.0025072593
6	(858.2，10.41)	0.0029384997
			7	(159，2.37)	0.0038991631
8	(186.9，2.44)	0.0045074080
			9	(609.1，1.44)	0.0047227895
10	(996.1，9.94)	0.0058177265
			11	(430.7，4.21)	0.0063024974
12	(141.1，5.13)	0.0068343584
			13	(839.6，20.85)	Q.0072422001
14	(956.1，10.62)	0.0080620376
			15	(113.2，0.44)	0.0081626136
16	(428.3，6.2)	0.0081962770
			17	(802.9，0.39)	0.0081962770
18	(819，2.11)	0.0081968739
			19	(366.1，0.86)	0.0084072673
20	(993.5，9.39)	0.0084773116
			21	(919.5，9.63)	0.0098988701
22	(680.6，7.39)	0.0105489986
			23	(523.3，22.32)	0.0105995251
24	(668.3，8.45)	0.0112292667
			25	(463.2，1.88)	0.0113722034
26	(259，11.71)	0.0115252694
			27	(889.7，16.16)	0.0115864528
28	(810.4，7.42)	0.0119405153
			29	(300，21.9)	0.0123871653
30	(141.2，1.46)	0.0124718161
			31	(785.5，9.3)	0.0126735996
32	(660.1，3.9)	0.0131662199
			33	(575.4，10)	0.0133539242
34	(398.2，8.89)	0.0133977345
			35	(678.8，2.37)	0.0134811753
36	(779.5，19.79)	0.0152076628
			37	(190.1，3.99)	0.0153485356
38	(746.8，2.42)	0.0153591871
			39	(407.2，7.81)	0.0154972293
40	(265.2，9.37)	0.0163877868
			41	(447.8，6.29)	0.0163877868
42	(472.5，11.18)	0.0166589145

43	(951.9，10.21)	0.0169717792
			44	(138.2，10.13)	0.0170020893
45	(739.5，9.45)	0.0171771560
			46	(999，7.71)	0.0177981470
47	(472.2，11.12)	0.0178902225
			48	(138.1，1.89)	0.0180631050
49	(842.9，6.93)	0.0189332371
			50	(717.3，17.96)	0.0193107546
51	(245.2，5.23)	0.0201247940
			52	(666.4，9.29)	0.0211733529
53	(820，6.38)	0.0216512533
			54	(991.7，9.21)	0.0219613529
55	(177，0.93)	0.0223857280
			56	(488.3，9.68)	0.0224061094
57	(119.1，9.19)	0.0224206599
			58	(278.1，5.24)	0.0240107773
59	(409.2，6.95)	0.0256235918
			60	(369.2，3.37)	0.0259379108
61	(482.4，19.26)	0.0261591305
			62	(806.6，21.29)	0.0269790713
63	(637.9，7.43)	0.0273533420
			64	(373.3，11.45)	0.0277220597
65	(264.2，8.83)	0.0282234106
			66	(909.7，6.36)	0.0282234106
67	(747.4，9.38)	0.0287012166
			68	(832.9，6.21)	0.0289271134
69	(155.1，2.87)	0.0289347031
			70	(977.7，9.56)	0.0298654782
71	(610.9，2.44)	0.0303741714
			72	(235.1，4.04)	0.0303830303
73	(685.1，6.85)	0.0303830303
			74	(670.4，9.09)	0.0307328580
75	(346.1，12.11)	0.0308972074
			76	(217.2，8.66)	0.0309517132
77	(770.9，16.6)	0.0310937661
			78	(163.2，6.31)	0.0313614024
79	(392.3，10)	0.0317350792
			80	(469.7，5.98)	0.0317350792
81	(470，6.32)	0.0317350792
			82	(794.9，9.76)	0.0317350792
83	(357.3，18.91)	0.0318983292
			84	(303.7，15.73)	0.0325397156
85	(221，1.92)	0.0328080364
			86	(999.5，7.28)	0.0330940901
87	(637.3，18.59)	0.0335078063
			88	(331，0.74)	0.0336148466
89	(978.8，6.72)	0.0338444022
			90	(271.1，15.08)	0.0347235687

91	(801，2.11)	0.0348606916
			92	(599.5，21.95)	0.0358839090
93	(769.4，10.46)	0.0371510791
			94	(914.1，6.94)	0.0375945952
95	(363，26.16)	0.0381998666
			96	(235.1，8.53)	0.0382752828
97	(273.2，6.31)	0.0390486612
			98	(250.1，14.23)	0.0401201887
99	(585.2，15.27)	0.0406073368
			100	(276.2，5.27)	0.0414046782
101	(183.1，6.88)	0.0419461253
			102	(430.3，9.1)	0.0421855472
103	(229.2，0.79)	0.0424445226
			104	(811.6，19.44)	0.0438285232
105	(126.2，4.02)	0.0439140255
			106	(708.5，15.79)	0.0439143789
107	(127，4.75)	0.0442108301
			108	(338.2，7.89)	0.0444291108
109	(391.3，14.55)	0.0444291108
			110	(714.6，14.02)	0.0444291108
111	(665.3，9.58)	0.0446481623
			112	(875.7，19.83)	0.0446481623
113	(676，6.65)	0.0447614386
			114	(695.1，2.71)	0.0448433123
115	(480.2，8.03)	0.0451624233
			116	(754.6，7.21)	0.0454753333
117	(494.9，19.41)	0.0454916992
			118	(785.1，9.29)	0.0455064285
119	(265.2，4.72)	0.0456621220
			120	(771.9，24.52)	0.0460254955
121	(467.2，8.55)	0.0464130076
			122	(869.9，10.55)	0.0464539626
123	(479.3，24.87)	0.0473472790
			124	(380.3，24.05)	0.0475242732
125	(194.1，6.48)	0.0475341652
			126	(262.6，5.7)	0.0475341652
127	(694.2，11.76)	0.0475341652
			128	(695.9，4.32)	0.0475341652
129	(660.8，2.32)	0.0475865516
			130	(958.8，6.36)	0.0482703924
131	(504.3，15.49)	0.0484159645

Table 13

The p value of the feature different: time-48 hour sample with baseline

Ion number	M/z (Da), retention time (min)	The p value
			1	(715.8，7.68)	0.0005303918
2	(919.5，9.63)	0.0012509535
			3	(802.4，8.16)	0.0016318638
4	(922.5，7.27)	0.0023943584
			5	(741.5，23.22)	0.0038457139
6	(875.4，19.37)	0.0044466656
			7	(878.9，7.28)	0.0052374088
8	(996.1，9.94)	0.0060309508
			9	(295.9，15.78)	0.0070608315
10	(521.4，23.84)	0.0075730074
			11	(676，6.65)	0.0075742521
12	(703.9，4.35)	0.0075743621
			13	(716.2，6.62)	0.0078671775
14	(346.1，7.46)	0.0080100576
			15	(551.4，24.89)	0.0086803932
16	(415.2，9.09)	0.0088869428
			17	(182.1，2.44)	0.0114906565
18	(310.3，19.13)	0.0121106698
			19	(428.3，6.2)	0.0124220037
20	(908.6，10.83)	0.0127529218
			21	(715.8，4.37)	0.0129735339
22	(444.3，2.8)	0.0135088012
			23	(753.3，9.34)	0.0140485313
24	(779.5，19.79)	0.0149169860
			25	(211.1，13.48)	0.0149614082
26	(285.2，19.8)	0.0155513781
			27	(441.4，19.09)	0.0169697745
28	(483.3，6.17)	0.0171647510
			29	(488.3，6.38)	0.0172240677
30	(616.2，11.9)	0.0176526391
			31	(861.8，9.74)	0.0185440613
32	(485.3，23.17)	0.0186867970
			33	(435.1，4.14)	0.0193706655
34	(612.3，16.87)	0.0193706655
			35	(362.3，5.65)	0.0194196263
36	(227，23.11)	0.0204130271
			37	(883.2，9.76)	0.0204386696
38	(229.2，0.79)	0.0205101165
			39	(643.3，5.67)	0.0210117164
40	(980.6，7.44)	0.0215182605
			41	(795.5，20.72)	0.0218437599
42	(577.2，3.56)	0.0224776501

43	(152.1，1.51)	0.0233549892
			44	(525.4，15.11)	0.0234730657
45	(435.3，19.92)	0.0235646539
			46	(299.2，25.54)	0.0237259148
47	(612.9，0.36)	0.0245420186
			48	(505.3，12.78)	0.0245629232
49	(986.7，7.42)	0.0248142595
			50	(719.2，6.07)	0.0252229441
51	(562.3，19.13)	0.0252471150
			52	(552.4，22.8)	0.0254361708
53	(353.2，19.3)	0.0266840298
			54	(575.4，16.74)	0.0275127383
55	(845.2，6.33)	0.0291304640
			56	(633.7，6.14)	0.0301224895
57	(519.3，13.32)	0.0301986537
			58	(205.1，13.28)	0.0306513410
59	(317.9，1.41)	0.0306513410
			60	(388.3，9.86)	0.0306513410
61	(471.3，26.3)	0.0306513410
			62	(723.2，6.69)	0.0320817369
63	(912.5，10.13)	0.0320817369
			64	(965.2，2.77)	0.0320817369
65	(718.9，5.76)	0.0322905214
			66	(363，26.16)	0.0330856794
67	(897.1，9.53)	0.0331382847
			68	(227.3，6.92)	0.0332507087
69	(778.2，14.75)	0.0335555992
			70	(321，2.35)	0.0337995708
71	(447.8，6.29)	0.0343295019
			72	(536.1，4.09)	0.0343295019
73	(653.5，19.99)	0.0343565954
			74	(667.4，21.32)	0.0343565954
75	(982.7，9.73)	0.0352875093
			76	(789.4，6.11)	0.0364395580
77	(505.3，18.48)	0.0369258233
			78	(277，0.2)	0.0369277075
79	(285.3，12.09)	0.0382728484
			80	(739.5，18.01)	0.0382728484
81	(838.9，0.39)	0.0382728484
			82	(400.2，5.79)	0.0384511838
83	(883.6，7.04)	0.0384732436
			84	(604.3，19.85)	0.0411740329
85	(287.1，4.72)	0.0412206143
			86	(549.9，4.23)	0.0415068077
87	(879.8，4.42)	0.0415426686
			88	(721.7，20.36)	0.0417134604
89	(711.4，16.81)	0.0417360498
			90	(982.1，9.39)	0.0419790105

91	(971.4，10.51)	0.0432043627
			92	(112.7，1.05)	0.0452851799
93	(503.3，14.33)	0.0453240047
			94	(173.1，23.44)	0.0466828436
95	(283.1，4.96)	0.0466865226
			96	(637.4，6.78)	0.0467959828
97	(597.4，15.92)	0.0471002889
			98	(813.5，9.83)	0.0480402523
99	(444.2，6)	0.0486844297
			100	(448.3，9.24)	0.0486916088
101	(502.5，4.01)	0.0493775335
			102	(854.2，5.79)	0.0493775335

Embodiment 2: use quantitative liquid chromatography (LC)-mass spectrum/mass spectrum (LC-MS/MS) to identify the protein biology mark

2.1 the sample of accepting and analyzing

As top, obtain the reference biomarker and compose from first colony (" SIRS group ") of forming by 15 patients with by suffering from SIRS and developing into second colony (" septicopyemia group ") that 15 patients of septicopyemia form.In the sky 1, time 0, time-48 hour draws blood from the patient.In this case, will be merged into four batches from patient's 50-75 μ L plasma sample: two batches respectively by 5 and 10 individual compositions, and these individualities all are the SIRS positives, are made up of 5 and 10 individualities for two batches, and these individualities all are septicopyemia-positives.Further analyze 6 samples criticizing from each merging.

2.2 specimen preparation

At first with the plasma sample immunodepletion to remove too much albumen, particularly albumin, Transferrins,iron complexes, haptoglobin, anti-trypsin, IgG and IgA, they form proteinic about 85% (wt%) in the sample together.(Agilent Technologies, Palo Alto California) implement immunodepletion, use this pillar according to manufacturer's explanation with Multiple Affinity Removal System post.Use this system to remove above-mentioned 6 kind proteinic at least 95% from plasma sample.For example, only about 0.1% albumin is retained in the sample of exhaustion.And the remaining high-abundance proteins of last only about 8% representative in the sample estimates is as IgM and α-2 macroglobulin.Use method as known in the art with plasma sample sex change, reduction, the alkylation of fractional separation and use tryptic digestion then.Obtain the albumen of about 2mg digestion from the sample of each merging.

2.3 multidimensional LC/MS

Then the peptide mixt behind the tryptic digestion is used LC post fractional separation also by Agilent MSD/ trap ESI-ion trap mass spectrometry with the LC/MS/MS alignment arrangements.With the 1mg digestible protein to be applied to miniflow C in 10 μ L/ minutes ₁₈Anti-phase (RP1) post.The series connection of RP1 post is coupled to strong cation exchange (SCX) fractional separation post, and this pillar is connected to C again conversely ₁₈The anti-phase post of catching.Sample is applied to the RP1 post with at RP1 column fractionation isolated peptides with first gradient of 0-10%ACN.Then be 10mM salt buffer wash-out after the ACN gradient, it becomes to be attached to the part of SCX post and is fixed on the elutriated fraction of catching post the further fractional separation of peptide.To catch then post from its with exercisable connection of SCX post remove and can be operatively connected with another C18 reversed-phase column (RP2).Catch post from this and be eluted on the RP2 post will catch in the post fixed fraction in 300nL/ minute with 0-10%ACN.This RP2 post is operably connected to AgilentMSD/trap ESI ion trap mass spectrometer, and this mass spectrograph is with the spray voltage operation of 1000-1500V.Use total ACN% to repeat this circulation (PR1-SCX-Trap-RP2) with fractional separation and separate remaining peptide from 0-80% with up to the salt concn of 1M.The suitable configuration of other of LC/MS/MS can be used for generation and can be used for biomarker spectrum of the present invention.The mass spectral m/z scope that produces is 200-2200Da.The scanning of application-dependent data and dynamic the eliminating to realize higher dynamicrange.Fig. 6 has shown the representative biomarker spectrum that produces with LC/MS and LC/MS/MS.

2.4 data analysis and result

For every kind of sample with the MS/MS pattern analysis, obtain about 150,000 kinds of spectrum, be equivalent to about 1.5 GB information.About 50 GB information have been collected altogether.(_ Copyright 2003 Agilent Technologies Inc.) analyze spectrum with SpectrumMill v 2.7 softwares.With MS-Tag database search algorithm (Millennium Pharmaceuticals) at the proteic database matching MS/MS spectrum of the people of NCBI (NCBI) nonredundancy.With the peptide that the score confirmation is mated that blocks that is equivalent to 95% degree of confidence, then with the albumen of described peptide assembling to exist in the evaluation sample.Be present in the blood plasma with the concentration of the detectable protein of the inventive method with～1ng/mL, the dynamicrange that covers plasma concentration is about 6 orders of magnitude.

By determining that the mass spectrum number to albumen " positive " obtains the sxemiquantitative estimation of detected protein abundance in the blood plasma.For for just, the intensity of ion characteristic can be higher than the noise at given m/z value place in the spectrum with detecting.Usually, in blood plasma with the higher level expressed protein as the positive ion feature or more multispectral in one group of ion characteristic will be to detect ground.By measuring of this protein concn, clearly multiple proteins is differentially expressed in SIRS organizes the septicopyemia group.Shown in Fig. 7 A and 7B that by the multiple detectable albumen of " rise " wherein the albumen that is raised is expressed with higher level than organizing at SIRS in the septicopyemia group.From Fig. 7 A can be clear that protein in time expression levels can with ion #21 (437.2Da, 1.42min) identical mode changes, ion #21 shows in Fig. 4.For example, protein with GenBank accession number AAH15642 and NP_000286 is structurally all similar to Serine (or halfcystine) proteinase inhibitor, in time with cumulative horizontal expression, and they reach with relative constant scale in the positive colony of SIRS-the both in septicopyemia-positive colony.Occur high-caliber these albumen in time in individuality, the especially expression of these proteic continuous risings is expected it is the predictor of septicopyemia outbreak.In Fig. 8 A and 8B, shown the multiple protein of in septicopyemia-positive colony, being reduced in time.These proteic some, in SIRS patient, seems cumulative or remain on high relatively level as unnamed protein expression, and this expression reduces in the septicopyemia patient with sequence shown in the GenBank accession number NP_079216.Expect that these protein will be especially to can be used for diagnosing SIRS, and the biomarker of prediction septicopyemia outbreak.

Embodiment 3: use antibody array identification of organism mark

3.1. the sample that receives and analyze

Be SIRS group and the upright reference biomarker spectrum of septicopyemia establishment.Per 24 hours from each study group's blood sample collection.The sample of gathering when comprising when entering research clinical signs of suspected same day (time 0) of preceding 48 hours of the clinical signs of suspected (time-48 hour) of (day 1), septicopyemia and septicopyemia outbreak from the sample of septicopyemia group.In this embodiment, SIRS group and the septicopyemia group analyzed in the time 0 comprise 14 and 11 individualities respectively, and the SIRSZ group and the septicopyemia group of hour analysis comprise 10 and 11 individualities respectively in time-48.

3.2 multichannel analysis

Use the multichannel analytical plan according to U.S. Patent number 5,981, the method of describing in 180 (" ' 180 patents ") is analyzed one group of biomarker in each sample in real time simultaneously, this patent intactly, especially its instruction about general method, pearl technology, system software and antibody test is merged in this paper as a reference.The immunoassay of describing in the patent of ' 180 is the representative that can be used for the immunoassay of the inventive method.In addition, the biomarker that is used for this paper is not limited to the scope that method of the present invention is used utilizable biomarker.About this analysis, synthetic matrix of microparticles, wherein this matrix not forming on the same group by particulate.Each group particulate on the surface of this particulate fixedly the different antibodies capture agent and by two kinds of fluorescence dyes that mix different amounts by color indicia.The ratio of two kinds of fluorescence dyes provides different emmission spectrum for every group of particulate, thereby allow to merge the particulate in the evaluation group behind multiple group of particulate.U.S. Patent number 6,268,222 and 6,599,331 are also incorporated into this paper as a reference by complete, and especially they are about the instruction of the several different methods of multichannel evaluation of markers particulate.

To merge and mix through the pearl of mark with plasma sample from the individuality that is used for this research.With the pearl single file pass flow-through appt, this device is with laser beam inquiry (interrogate) each particulate of fluorescence excitation group mark, thereby identifies the pearl through mark.Fluorescence detector detects the emmission spectrum of each pearl so that these pearls are divided into suitable group then.Because the identity for every kind of antibody capture reagent of every group of particulate is known, so the specificity of every kind of antibody and the discrete particle coupling of passing flow-through appt.U.S. Patent number 6,592,822 also by intactly, and the instruction of multiple analyte diagnositc system that especially can be used for the multichannel analysis of the type is merged in this paper as a reference.

In order to determine to be attached to the amount of analyte of given group particulate, add reporter molecules, thereby the antibody of this report molecule and the analyte separately that is attached to them forms complex body.In this example, reporter molecules is the secondary antibody through the fluorophore mark.By the fluorophore on another laser excitation reporter molecules with different excitation wavelengths, thereby allow the fluorophore mark on the secondary antibody to make a distinction with the fluorophore that is used for labeled microparticles.Another fluorescence detector detects the emission of fluorophore mark on this secondary antibody, to determine to form by capture antibody and bonded analyte the amount of the secondary antibody of complex body.Like this, can be fast and in single reaction, detect the amount of the multiple analytes that pearl catches in real time.

3.3 data analysis and result

For every kind of sample, detect concentration in conjunction with the analyte of 162 kinds of different antibodies.In this example, every kind of analyte all is a biomarker, and the concentration of every kind of biomarker can be a kind of feature of this biomarker in the sample.Analyze biomarker with 162 kinds of listed in the following table 14 antibody reagents, these reagent can be by commercial sources from Rules Based Medicine ofAustin, and Texas obtains.Antibody reagent is classified as circulating protein matter biomarker component in specific combination (1) blood, (2) (identify in conjunction with the circulating antibody of the molecule relevant usually by every kind of biomarker bonded cause of disease with multiple cause of disease, the autoantibody biomarker that as shown), perhaps (3) are relevant with various disease states.

Table 14

(1) circulation serum component

Alpha-fetoprotein

APoA 1

ApoC III

Apolipoprotein H

Beta-2 microglobulin

The neurotrophic factor in brain-source

Complement 3

Cancer antigen 125

Carcinomebryonic antigen (CEA)

Creatine kinase-MB

Corticotropin releasing factor(CRF)

C reactive protein

Epithelium neutrophilic granulocyte activating peptide-78 (ENA-78)

Fatty acid binding protein

Factor VII

Ferritin

Fibrinogen

Tethelin

CM-CSF

Glutathione S-transferase

Intercellular adhesion molecule 1 (ICAM 1)

Immunoglobulin A

Immunoglobulin E

Immunoglobulin M

Interleukin-10

Il-1 2p 40

Il-1 2p 70

Interleukin-13

Interleukin-15

IL-16

Il-1 8

Il-1 α

Il-1 β

Interleukin-2

Interleukin-3

Interleukin-4

Interleukin-5

Interleukin-6

Interleukin-7

Interleukin-8

Regular Insulin

Leptin (Leptin)

Lipoprotein (a)

Lymphotactin

Scavenger cell chemical attractants albumen-1 (MCP-1)

The chemokine in scavenger cell-source (MDC)

Macrophage inflammatory protein-1 β (MIP-1 β)

Matrix metalloproteinase-3 (MMP-3)

Matrix metalloproteinase-9 (MMP-9)

Myohaemoglobin

Prostate acid phosphatase

Prostate specific antigen, free

Be conditioned normal T-cell expressing and excretory (RANTES) during activation

Serum amyloid shape albumen P

STEM CELL FACTOR

Serum glutamic oxalacetic transaminase (SGOT)

Thyroid binding globulin

The tissue depressant of metalloprotease 1 (TIMP1)

Tumor necrosis factor-alpha (TNF-α)

Tumour necrosis factor-β (TNF-β)

Thrombopoietin

Thyrotropin (TSH)

Feng. von Willebrand (von Willebrand) factor

(2) in conjunction with the antibody of indicated cause of disease mark

Adenovirus

Bordetella pertussis

Campylobacter jejuni

Chlamydia pneumoniae

Chlamydia trachomatis

Toxins,exo-, cholera

Toxins,exo-, cholera (B of subunit)

Cytomegalovirus

Diphtheria toxin

Epstein-Barr virus-capsid antigen

Epstein-Barr virus is antigen early

Eb nuclear antigen

Helicobacter pylori

HBc

The hepatitis B tunicle

HBS (Ad)

HBS (Ay)

The hepatitis C core

The non-structure 3 of hepatitis C C

The non-structure 4 of hepatitis C C

The non-structure 5 of hepatitis C C

Hepatitis D

Hepatitis A

Hepatitis E E virus (orf2 3KD)

Hepatitis E E virus (orf2 6KD)

Hepatitis E E virus (orf3 3KD)

Human immunodeficiency virus-1 p24

Human immunodeficiency virus-1 gp120

Human immunodeficiency virus-1 gp41

Human papillomavirus

Hsv-1/2

Hsv-1gD

Hsv-2gG

People T-cell is had a liking for lymphocyte virus 1/2

Influenza A

Influenza A H3N2

Influenza B

The Gan Shi leishmania

Lyme borrelia burgdorferi disease

The pneumonia mycobacterium

Mycobacterium tuberculosis

Mumps virus

Parainfluenza virus 1

Parainfluenza virus 2

Parainfluenza virus 3

Poliovirus

Respiratory syncytial virus

Rubella virus

Measles virus

Streptolysin O (SLO)

Trypanosoma cruzi

Tyreponema pallidum 15KD

Tyreponema pallidum p47

Tetanus toxin

Toxoplasma gondii

The varicella herpes zoster

(3) autoantibody

Anti-yeast saccharomyces cerevisiae (Saccharomyces cerevisiae) antibody (ASCA)

Anti--β-2 glycoprotein

Anti--the kinetochore PROTEIN B

Anti--collagen 1 type

Anti--collagen 2 types

Anti--collagen 4 types

Anti--collagen 6 types

Anti--C1Q

The anti-cell cytochrome p 450

Anti--double-stranded DNA (ds DNA)

Anti--histone

Anti--histone h1

Anti--histone H2a

Anti--histone H2b

Anti--histone H 3

Anti--histone H 4

Anti--heat-shocked associated protein 70 (HSC 70)

Anti--heat shock protein(HSP) 32 (HO)

Anti--heat shock protein(HSP) 65

Anti--heat shock protein(HSP) 71

Anti--heat shock protein 90 α

Anti--heat shock protein 90 β

Anti-insulin-

Anti--Histidyl-tRNA synthetase (JO-1)

Anti--plastosome

Anti--myeloperoxidase (all autoantibodies of the antigenic nuclear of neutrophilic granulocyte endochylema)

Anti--islet cells (Glutamic Acid Decarboxylase autoantibody)

Anti--proliferating cell nuclear antigen (PCNA)

Polymyositis-1 (PM-1)

Anti--protease 3 (the antigenic endochylema autoantibody of neutrophilic granulocyte endochylema)

Anti--rrna P

Anti--ribonucleoprotein (RNP)

Anti--ribonucleoprotein (a)

Anti--ribonucleoprotein (b)

Anti--topoisomerase I (Scl 70)

Anti--ribonucleoprotein Smith Ag (Smith)

Anti--Sj_gren Cotard A (Ro) is (SSA)

Anti--Sj_gren Cotard B (La) is (SSB)

Anti--T3

Anti--T4

Anti-Thyroglobulin

The Anti-Thyroid microsome

Anti--tTG (tissue transglutaminase, coeliac disease)

Can identify some features with several different methods, wherein these features can be for providing information with individual segregation for the decision rules of SIRS or septicopyemia group.Selected method is the signed rank test of logistic regression and Wilcoxon.

3.3.1 use the logistic regression analytical data

Use logistic regression to analyze the quantitative result that obtains from the biomarker immunoassay.Listed 26 kinds of biomarkers of time 0 colony in the table 15, they contain the pattern with SIRS and septicopyemia differentiation.For time-48 hour, contain 14 kinds of biomarkers that SIRS and septicopyemia are distinguished and in table 16, list.Data interpretation in the table 15 and 16 contain those biomarkers of the pattern of distinguishing SIRS and septicopyemia group.

Table 15

The biomarker that contains pattern: time 0 sample

Biomarker	Importance
		Myohaemoglobin	0.1958
Matrix metalloproteinase (MMP)-9	0.1951
		Macrophage inflammatory protein-1 β (MIP-1 β)	0.1759
The C-reactive protein	0.1618
		Interleukin (IL)-16	0.1362
Hsv-1/2	0.1302
		Anti--C1Q antibody	0.1283
PCNA (PCNA) antibody	0.1271
		The former 4 type antibody of anticol	0.1103
The tissue depressant of metalloprotease-1 (TIMP-1)	0.1103
		Glutathione S-transferase (GST)	0.1091
Anti-yeast saccharomyces cerevisiae (Saccharomyces cerevisiae) antibody (ASCA)	0.1034
		Tethelin (GH)	0.1009
Poliovirus	0.0999
		IL-18	0.0984
Thyroid binding globulin	0.0978
		Anti--tTG (tissue transglutaminase, coeliac disease) antibody	0.0974
Leptin	0.0962
		Anti--histone H2a antibody	0.0940
B2M	0.0926
		Helicobacter pylori	0.0900
Diphtheria toxin	0.0894
		The hepatitis C core	0.0877
Serum glutamic oxalacetic transaminase	0.0854
		The non-structure 3 of hepatitis C	0.0845
The non-structure 4 of hepatitis C	0.0819

Table 16

The biomarker that contains pattern: time-48 hour sample

Biomarker	Importance
		Thyroid binding globulin	0.0517
IL-8	0.0414
		Intercellular adhesion molecule 1 (ICAM 1)	0.0390
Prostate acid phosphatase	0.0387
		MMP-3	0.0385
Hsv-1/2	0.0382
		C reactive protein	0.0374
MMP-9	0.0362
		Anti-PCNA antibody	0.0357
IL-18	0.0341
		ASCA	0.0341
Lipoprotein (a)	0.0334
		Leptin	0.0327
Tetanus toxin	0.0326

3.3.2 use the signed rank test analytical data of Wilcoxon

Identify single target protein biology mark with the signed rank test of Wilcoxon.With with top embodiment 1.4.7 in table 8-10 identical mode, septicopyemia and SIRS colony give that listed biomarker distributes the p value in the table 14 during by preset time relatively.Analyze for this, the septicopyemia of 0 o'clock time and SIRS colony (table 17) are made up of 23 and 25 patients respectively; Septicopyemia and SIRS colony (table 18) during time-24 hour are made up of 25 and 22 patients respectively; Septicopyemia and SIRS colony (table 19) during time-48 hour are made up of 25 and 19 patients respectively.

Table 17

The biomarker p value of time 0 sample

Biomarker	The p-value
		IL-6	2.1636e-06
C reactive protein	1.9756e-05
		TIMP-1	7.5344e-05
IL-10	8.0576e-04
		Thyrotropin	0.0014330
IL-8	0.0017458
		MMP-3	0.0032573
MCP-1	0.0050354
		Glutathione S-transferase	0.0056200
MMP-9	0.0080336
		Beta-2 microglobulin	0.014021
Histone H2a	0.023793
		MIP-1β	0.028897
Myohaemoglobin	0.033023
		C1Q	0.033909
ICAM-1	0.036737
		Leptin	0.046272
ApoC III	0.047398

Table 18

The biomarker p-value of time-24 hour sample

Biomarker	The p-value
		IL-6	0.00039041
TIMP-1	0.0082532
		C1Q	0.012980
Thyrotropin	0.021773
		HSC 70	0.031430
SSB	0.033397
		MMP-3	0.035187
Thyrocalcitonin	0.038964
		Thrombopoietin	0.040210
Factor VII	0.040383
		Histone H2a	0.042508
Fatty acid binding protein	0.043334

Table 19

The biomarker p-value of time-48 hour sample

Biomarker	The p-value
		IL-8	0.0010572
C reactive protein	0.0028340
		IL-6	0.0036449
ICAM-1	0.0056714
		MIP-1β	0.016985
Thyroid binding globulin	0.025183
		Prostate specific antigen, free	0.041397
APoA 1	0.043747

In addition, the p-value is based on the continuous appearance or the disappearance of feature in the colony of septicopyemia development, and is identical with the mode of showing among the 11-13 among the embodiment 1.4.7.Analyze for this, group size with top shown in identical, just time-48 hour septicopyemia and SIRS colony are made up of 22 and 18 patients respectively.

Table 20

The p-value of the feature different: time 0 sample with baseline

Biomarker	The p-value
		C reactive protein	0.0088484
MMP9	0.022527
		T3	0.043963

Table 21

The p-value of the feature different: time-24 hour sample with baseline

Biomarker	The p-value
		Feng. von Willebrand (von Willebrand) factor	0.0047043
HIV1 gp41	0.011768
		Islet cells GAD	0.030731
Creatine kinase mb	0.043384
		Apolipoprotein H	0.046076

Table 22

The p-value of the feature different: time-48 hour sample with baseline

Biomarker	The p-value
		Islet cells GAD	0.00023455
T3	0.0010195
		HIV1 p24	0.031107
Hepatitis A	0.045565
		Ferritin	0.048698

3.3.3 use flexible regression tree (MART) analytical data

As describing among the top embodiment 1.4.5, analyzed from the data of time 0 sample gained protein biomarker spectrum with MART.In this was analyzed, 0 hour time, septicopyemia colony was made up of 23 patients, and SIRS colony is made up of 25 patients.Analyzed feature corresponding to all 164 kinds of biomarkers in the table 14.Model of fit comprises 24 trees, and this model does not allow the interaction in the feature.Use ten times of cross validations, this model has correctly been sorted out 17 among among 25 SIRS patients 17 and 23 the septicopyemia patients, and model sensitivity is 74%, and specificity is 68%.The importance of determining according to this model in table 23 is arranged biomarker.Get rid of all features with 0 importance.The mark of pointing out with symbol " 1 " is along with the expression level of development in the positive colony of septicopyemia of septicopyemia constantly raises, and the marker expression level of pointing out with symbol " 1 " constantly reduces.

Table 23

Feature importance by the MART analysis: 0 hour time sample

Biomarker	Importance	Symbol
			C reactive protein	32.281549	1
Thyrotropin	11.915463	-1
			IL-6	11.284493	1
MCP-1	11.024095	1
			Beta-2 microglobulin	7.295072	1
Glutathione S-transferase	5.821976	1
			Serum amyloid protein P	5.546475	1
IL-10	4.771469	1
			TIMP-1	4.161010	1
MIP-1β	3.040239	1
			ApoC III	2.858158	-1

Embodiment 4: use SELDI-TOF-MS identification of organism mark

4.1 specimen preparation and experimental design

The method according to this invention, SELDI-TOF-MS (SELDI) provides the another kind of method of septicopyemia in definite individuality or SIRS state.Predicted characteristics in the biomarker spectrum of the non-folk prescription method identification of organism sample of SELDI permission use.With sample ionization, detect ionic m/z by laser beam then.The biomarker spectrum that contains different kinds of ions then by top any Algorithm Analysis.

Use WCX2 example platform has been described, perhaps the representative SELDI experiment of " chip ".Every type chip adsorpting characteristic biomarker; Therefore, according to the chip of used particular type, can obtain different biomarker spectrums from same sample.Each conventional scheme is from PPTTM Vaeutainer ^TMThe blood of collecting in the pipe (Becton, Dickinson and Company, FranklinLakes, New Jersey) prepares blood plasma (500 μ L).Blood plasma is divided into 100 μ L aliquots containigs and-80 ℃ of preservations.According to manufacturer's scheme, use Biomek 2000 robots (Beckman Coulter) in the Ciphergen biological processor, prepare the WCX-2 chip (Ciphergen Biosystems, Inc., Fremont, California).The WCX-2 chip has 8 binding sites.Point on the chip with 50 μ L, 50% acetonitrile continuous washing twice, each 5 minutes, with 50 μ L 10mM HCl washing 10 minutes, is used 50 μ L deionized water wash 5 minutes then at last.After the washing, before importing plasma sample, regulate twice, each 5 minutes with 50 μ L WCX2 damping fluids.In table 24, provided the lavation buffer solution of WCX2 chip and other chip types (comprising H50, IMAC and SAX2/Q10 chip).

Table 24

Chip type	The SELDI lavation buffer solution
		IMAC3	Phosphate buffered saline(PBS), pH7.4,0.5M NaCl and 0.1% Triton X-100
WCX2	The 20mM ammonium acetate, pH6.0 contains 0.1%Triton X-100
		SAX2/Q10	The 100mM ammonium acetate, pH4.5
H50	0.1M NaCl, 10%ACN and 0.1% trifluoroacetic acid

Each some adding 10 μ L plasma sample on the WCX-2 chip through regulating and 90 μ LWCX-2 binding buffer liquid (20mM ammonium acetate and 0.1%Triton X-100, pH6.0).Vibration after 30 minutes, with 100 μ L WCX-2 binding buffer liquid washing point twice, is used twice of 100 μ L deionized water wash in incubated at room down then.Then that chip is dry and use substrate material, as α-cyanogen hydroxycinnamic acid (99%) (CHCA) or twice of the saturated solution 0.75 μ L point sample of sinapinic acid (SPA) in 50% acetonitrile, 0.5%TFA aqueous solution.Use then experiment condition shown in the table 25 by SELDI-TOF-MS to chip reading in conjunction with plasma proteins.

Table 25

SELDI reading condition

Experiment is provided with	Matrix: SPA	Matrix: CHCA
				Detect voltage	2850V	2850V	2850V
The deflector quality	1000Da	1000Da	1000Da
				Quanxtizer speed	500MHz	500MHz	500MHz
High quality	75,000Da	75,000Da	75,000Da
				Focusing quality	6000Da	30,000Da	30,000Da
Intensity (low/height)	200/205	160/165	145/150
				Sensitivity (low/height)	6/6	6/6	6/6
Emission/point that keeps	91/65	91/65	91/65

Table 26-49 has shown the p-value of the SELDI experiment of under the listed condition plasma sample being implemented in table 25.Shown chip type in each table, they are WCX-2, H50, Q10 or IMAC.For every kind of chip, implement experiment with CHCA matrix, high-octane SPA matrix (seeing Table 25) or low-energy SPA matrix.In addition, for every kind of matrix, analyzed the sample of 0 hour time, time-24 hour, time-48 hour.Use nonparameter test to determine the p-value of determining for listed ion, this nonparameter test is the signed rank test of Wilcoxon in this case.Only listed corresponding p-value less than 0.05 ion (following table empty grid shows that those ionic p-value in the sample is not less than 0.05).At last, in every kind of sample,, be marked as " the p-value of the feature different " (in table 1.4.7) in these p values table below as preceding with baseline to the different distribution p values of characteristic strength in septicopyemia colony and the SIRS colony and baseline.In table the experimental error of listed m/z value be about ± 2%.

Table 26

SELDI biomarker p value: WCX-2 chip

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	2290.1	0.000438	2579.4	0.001681	2004.6	0.000166
2	3163.9	0.000438	3357.4	0.001681	2004	0.000448
							3	6470.6	0.000438	3340.9	0.001826	2005.5	0.000448
4	1773.1	0.000917	1394.6	0.00295	1935.7	0.000916
							5	2623.8	0.001253	2195.7	0.003188	1909.1	0.001011
6	4581.4	0.002823	2818.6	0.004009	1892.3	0.001629
							7	6474.2	0.00303	17107	0.005392	2003.5	0.001787
8	1645	0.003997	2220.2	0.005392	1939.1	0.002348
							9	3065.5	0.004278	18688	0.006229	2035.4	0.002348
10	2775.1	0.004576	2613.3	0.007179	2011.7	0.002567
							11	6435.5	0.004893	5827.3	0.007179	2042.4	0.003061
12	3195.9	0.006362	5894.2	0.007701	1916.1	0.003338
							13	3781.7	0.006362	5892.8	0.01013	2041.5	0.003637
14	6780.5	0.006362	2813.9	0.011578	1848.6	0.003959
							15	1657.1	0.007706	3728.9	0.011578	2041.8	0.004307
16	2579.4	0.007706	1401	0.012367	1722.7	0.005084
							17	1628.9	0.008735	1726.1	0.012367	1877.1	0.005084
18	5901.2	0.008735	6673.1	0.013202	1911.2	0.005084
							19	6667.5	0.008735	2806	0.014086	6676.7	0.005084
20	2438.8	0.010504	5897.8	0.014086	1878.3	0.005517
							21	2793.8	0.010504	37828	0.01502	1879.2	0.005517
22	2811.5	0.010504	6674.5	0.01502	1692	0.005982
							23	1627.8	0.01116	2705.9	0.016007	2003.1	0.005982
24	3085.5	0.01116	2793.8	0.016007	2039.2	0.005982
							25	3218.6	0.01116	5885.2	0.017049	2042.1	0.005982
26	5885.2	0.01116	6474.2	0.017049	6674.5	0.005982
							27	5894.2	0.01185	3331.5	0.018149	2101.2	0.007016
28	2798.3	0.012578	3718.9	0.018149	1879.5	0.00759
							29	5897.8	0.012578	5891.2	0.018149	2008.4	0.00759
30	3336.2	0.013343	5901.2	0.020532	1687.5	0.008204
							31	3974.5	0.013343	5902.2	0.02182	1689.9	0.008204
32	7483.6	0.013343	5889.9	0.023176	1878.8	0.008861
							33	1379.4	0.014149	2039.2	0.026105	4858.8	0.008861
34	3235.8	0.014149	4560.7	0.026105	1855.2	0.009563
							35	3238.3	0.014149	5850.4	0.026105	2432	0.009563
36	3761.8	0.014997	3769.5	0.027683	1888.2	0.010314
							37	5892.8	0.014997	11639	0.029341	1657.1	0.011115
38	3319.9	0.015888	3346.9	0.029341	1719.7	0.01197
							39	1394.6	0.016824	4574.2	0.029341	1879.7	0.01197

40	3333.5	0.017807	6676.7	0.029341	1609.2	0.01288
							41	1946.9	0.01884	4567.4	0.031082	2015.1	0.01288
42	2238.6	0.01884	2342.5	0.032909	3333.5	0.01288
							43	3299.6	0.01884	2811.5	0.032909	2002.2	0.01385
44	5827.3	0.01884	2340.9	0.034824	2018.1	0.01385
							45	3205.2	0.019923	2474.5	0.034824	6673.1	0.01385
46	2274.7	0.021059	2168.3	0.036832	1341.2	0.014882
							47	2813.9	0.021059	2683	0.038936	1883.3	0.014882
48	3331.5	0.021059	3038.5	0.038936	3331.5	0.014882
							49	3780.6	0.022249	3753.8	0.038936	1380.6	0.01598
50	1724.7	0.023497	2340.1	0.041138	1923.2	0.01598
							51	2678.1	0.023497	3412.9	0.041138	3582	0.01598
52	5889.9	0.023497	6470.6	0.041138	1354.4	0.018385
							53	2673.4	0.024804	6691.5	0.041138	1605.9	0.018385
54	6635.1	0.026171	1605.1	0.043443	1606.5	0.018385
							55	1793.8	0.027603	3450.1	0.043443	1371.1	0.019699
56	2976.7	0.027603	1399.5	0.045854	1940.2	0.019699
							57	2359.7	0.029099	1402	0.045854	3085.5	0.019699
58	5891.2	0.029099	7637.9	0.045854	6470.6	0.019699
							59	1627	0.030664	4871.3	0.048373	1384.2	0.021093
60	2654.3	0.030664	5810	0.048373	1913.7	0.021093
							61	5030.1	0.030664	5867.2	0.048373	2045.1	0.021093
62	5748.8	0.030664	6667.5	0.048373	2051.4	0.021093
							63	5962.8	0.030664			1125.7	0.022569
64	3315.7	0.032299			1781.2	0.022569
							65	5564.3	0.034006			6780.5	0.022569
66	2538.5	0.035789			1779.1	0.024132
							67	6561.5	0.035789			2469.2	0.024132
68	3094.3	0.037649			2775.1	0.025786
							69	1827.7	0.039588			1777.8	0.027535
70	5837.7	0.039588			1836.1	0.027535
							71	5514.7	0.041611			1420.4	0.031332
72	1472.3	0.043718			2059.5	0.031332
							73	2208.4	0.043718			6474.2	0.031332
74	2660.4	0.043718			1694.9	0.03339
							75	2951.7	0.043718			1917.4	0.03339
76	1273.2	0.045912			2768.8	0.03339
							77	1625.3	0.045912			3126	0.03339
78	1630.7	0.045912			4862.4	0.03339
							79	5528.5	0.045912			2029.5	0.035559
80	1626.1	0.048197			1175.8	0.037845
							81	2195.7	0.048197			1875.7	0.037845
82	2818.6	0.048197			1880.7	0.037845
							83	3758.9	0.048197			1688.3	0.040251
84					2033.4	0.040251
							85					5058	0.040251
86					5129.9	0.040251
							87					1602.6	0.042783

88					4370.5	0.045445
							89					10261	0.048242
90					1991.2	0.048242
							91					2062.3	0.048242
92					3485.1	0.048242

Table 27

SELDI biomarker p value: WCX-2 chip

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	5308.9	0.001309	2802	0.004655	7300.2	0.01197
2	5302.8	0.001416	6777.8	0.005011	7642.6	0.01385
							3	5357.6	0.00193	3386.7	0.008254	7651.1	0.01385
4	5335.1	0.002082	5302.8	0.008843	12194	0.014882
							5	5324.4	0.002805	37933	0.01013	7653.8	0.014882
6	5316.6	0.003244	7603	0.01013	11591	0.017146
							7	5379.4	0.004017	2834.7	0.010833	7624.5	0.018385
8	37933	0.00462	6838.2	0.01502	7658.6	0.019699
							9	5312.5	0.006071	7132.1	0.01502	7469.1	0.022569
10	5388.9	0.006071	11676	0.016007	11628	0.027535
							11	5222.9	0.008998	74907	0.016007	12385	0.027535
12	5372.2	0.008998	1138	0.018149	7665.2	0.031332
							13	5232.4	0.009591	1893.8	0.019309	11635	0.035559
14	11591	0.010217	1005.9	0.023176	3669.3	0.040251
							15	11880	0.011577	6819.8	0.023176	4200.7	0.042783
16	11272	0.012314	7126.6	0.024604	4214	0.045445
							17	12385	0.014775	7711.6	0.026105	7862.1	0.045445
18	5343	0.014775	2893.6	0.027683	7496.4	0.048242
							19	10509	0.015685	5286.1	0.027683	7682.9	0.048242
20	5349.2	0.020991	6604.5	0.027683
							21	5878.5	0.020991	7140.1	0.027683
22	5295	0.023506	9281	0.027683
							23	5894	0.023506	1009.6	0.029341
24	11773	0.026274	3588	0.029341
							25	37131	0.026274	29435	0.031082
26	5260.6	0.027758	30235	0.031082
							27	5902.3	0.027758	3360.7	0.031082
28	5910.4	0.029312	5277.2	0.031082
							29	5906.8	0.034422	1069.6	0.032909
30	5254.8	0.036282	50968	0.032909
							31	5277.2	0.036282	65913	0.032909
32	10631	0.044585	7582.4	0.032909

33	11628	0.04689	1014	0.034824
							34	5240	0.04689	7122.3	0.034824
35	9487.6	0.04689	5056.1	0.036832
							36	12588	0.049292	7113.7	0.036832
37	15094	0.049292	73096	0.036832
							38	5271.3	0.049292	3369.2	0.038936
39	5885.5	0.049292	5324.4	0.038936
							40			6985.9	0.038936
41			6998.9	0.038936
							42			7682.9	0.038936
43			1003.5	0.041138
							44			11641	0.041138
45			3639.3	0.041138
							46			3945.5	0.041138
47			3952.5	0.041138
							48			7149.2	0.041138
49			5240	0.043443
							50			6959.8	0.043443
51			77136	0.043443
							52			11716	0.045854
53			14244	0.045854
							54			4269.7	0.045854
55			9194.8	0.048373

Table 28

SELDI biomarker p value: WCX-2 chip

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	3490.7	0.000339	1685.2	0.000848	1882.6	0.002804
2	5356.2	0.001655	6722.9	0.000926	2671.1	0.002804
							3	3033.8	0.001788	4584.8	0.001201	2101	0.005084
4	37873	0.001788	12256	0.001423	62628	0.005517
							5	5264	0.002606	1182.2	0.001981	2787.9	0.008204
6	7560.1	0.002805	1633.6	0.001981	9900.3	0.008861
							7	19083	0.003017	1683.8	0.002148	3077.6	0.01598
8	3681.1	0.004309	1686.4	0.002328	2775.5	0.017146
							9	2469.6	0.005302	6938.4	0.002328	5810.7	0.017146
10	2583.7	0.006071	4580	0.002521	2274.5	0.018385
							11	2379.3	0.006936	4588.7	0.002521	2635.1	0.021093
12	9126.4	0.007408	6705.1	0.002521	2615.7	0.022569
							13	11836	0.007909	9155	0.002521	1679.4	0.024132
14	3980.6	0.007909	1949.5	0.003717	2528.2	0.024132
							15	2604.6	0.008998	2553.8	0.003717	1838.9	0.027535

16	2573.3	0.010879	9687.7	0.004009	3410.6	0.027535
							17	3084.4	0.010879	1593.2	0.004655	7560.1	0.027535
18	11578	0.013092	1946.2	0.004655	1821.2	0.031332
							19	3986	0.013092	9605.1	0.004655	1253.9	0.03339
20	5903.8	0.013092	2799.9	0.005797	1823	0.03339
							21	5907.6	0.013092	6750.5	0.006229	3599.6	0.03339
22	5909.7	0.013092	1477.6	0.00669	6697.9	0.03339
							23	7554.1	0.013092	2196.2	0.00669	1388.9	0.037845
24	2683.7	0.013912	2735.6	0.00669	1818.3	0.037845
							25	5268.7	0.013912	2960.8	0.00669	5268.7	0.037845
26	1627	0.014775	6702.5	0.00669	5903.8	0.040251
							27	6969.7	0.014775	1925.8	0.007701	6694.6	0.040251
28	2663.3	0.015685	2811.2	0.007701	11472	0.042783
							29	3017.9	0.016642	2193.3	0.008254	11489	0.042783
30	5250.5	0.016642	3042	0.008254	11532	0.042783
							31	5906.1	0.016642	2809.6	0.008843	11578	0.042783
32	9129	0.017649	2170.5	0.009468	37873	0.042783
							33	2600.8	0.018709	2831.5	0.009468	6699.7	0.042783
34	3977.8	0.018709	3364.2	0.009468	6701	0.042783
							35	5321.3	0.018709	4573.6	0.009468	1253.1	0.045445
36	7636.7	0.018709	2809.3	0.01013	7622.6	0.045445
							37	9108.6	0.019822	2809.8	0.01013	10098	0.048242
38	2697.6	0.020991	1471.6	0.010833	1863	0.048242
							39	7564.6	0.020991	2064.9	0.010833	2055.5	0.048242
40	2815.7	0.022218	2791.7	0.010833	3104.4	0.048242
							41	1829.3	0.023506	2801.3	0.010833
42	11797	0.024858	37873	0.010833
							43	5991.8	0.024858	6508.4	0.010833
44	2281.6	0.026274	6701	0.010833
							45	2996.8	0.026274	2171.9	0.011578
46	1898.4	0.029312	4595.5	0.011578
							47	3991.5	0.029312	4865.3	0.011578
48	1987.2	0.030939	7170.7	0.011578
							49	7244.8	0.030939	1688.5	0.012367
50	2320.5	0.032642	17749	0.012367
							51	25044	0.032642	2806.4	0.012367
52	2505.3	0.032642	6699.7	0.012367
							53	4564.4	0.032642	6951.3	0.012367
54	5900.8	0.032642	1701.2	0.013202
							55	6977.4	0.032642	2795.9	0.013202
56	1666.5	0.034422	6509.3	0.013202
							57	10098	0.036282	1877.3	0.014086
58	1995.7	0.038226	19083	0.014086
							59	2582.4	0.038226	2173.6	0.014086
60	11766	0.040256	3017.9	0.014086
							61	3575.5	0.040256	4600.9	0.014086
62	5911.6	0.040256	1567.6	0.01502
							63	2546.6	0.042375	2808.7	0.01502

64	3047.9	0.044585	6697.9	0.01502
							65	8298.4	0.044585	1220.4	0.016007
66	11472	0.04689	1460.3	0.016007
							67	11732	0.04689	1460.7	0.016007
68	2151.8	0.04689	2184.9	0.016007
							69	2171.9	0.04689	3025.6	0.016007
70	2681.6	0.04689	3355.4	0.016007
							71	3021.1	0.04689	3367.9	0.016007
72	3410.6	0.04689	3871.9	0.016007
							73	3913	0.04689	4900.9	0.016007
74	4911	0.04689	6506.1	0.016007
							75	9132.4	0.04689	1664	0.017049
76	4670.1	0.049292	6926.2	0.017049
							77	7566.2	0.049292	3021.1	0.018149
78			3490.7	0.018149
							79			4592.3	0.018149
80			9834.1	0.018149
							81			2813.6	0.019309
82			3362	0.019309
							83			9230.4	0.019309
84			10661	0.020532
							85			1454.4	0.020532
86			1595.8	0.020532
							87			2719	0.020532
88			3030.9	0.020532
							89			5297.9	0.020532
90			6771.4	0.020532
							91			7106.1	0.020532
92			97077	0.020532
							93			1234.5	0.02182
94			1684.7	0.02182
							95			1947.7	0.02182
96			2803.1	0.02182
							97			6514.8	0.02182
98			7669.7	0.02182
							99			2180	0.023176
100			2817.9	0.023176
							101			2841	0.023176
102			3442.4	0.023176
							103			6502.2	0.023176
104			2287.5	0.024604
							105			3939.8	0.024604
106			5215.7	0.024604
							107			1772.5	0.026105
108			2397.5	0.026105
							109			2692.2	0.026105
110			3009.7	0.026105
							111			3945.3	0.026105

112			3973.5	0.026105
							113			9900.3	0.026105
114			1478.3	0.027683
							115			1690.2	0.027683
116			2443.3	0.027683
							117			4002.7	0.027683
118			6192.3	0.027683
							119			6527.3	0.027683
120			6694.6	0.027683
							121			9639.8	0.027683
122			1416.4	0.029341
							123			1476.4	0.029341
124			1699.9	0.029341
							125			3748.9	0.029341
126			4734.4	0.029341
							127			6566	0.029341
128			11615	0.031082
							129			1233.7	0.031082
130			1448.7	0.031082
							131			1863.6	0.031082
132			2486.9	0.031082
							133			2815.7	0.031082
134			2826.4	0.031082
							135			11648	0.032909
136			1181.3	0.032909
							137			1431.3	0.032909
138			1457.3	0.032909
							139			1479.5	0.032909
140			2978.7	0.032909
							141			74349	0.032909
142			8280.7	0.032909
							143			9132.4	0.032909
144			9994.9	0.032909
							145			2092.8	0.034824
146			2225	0.034824
							147			1669.8	0.036832
148			3104.4	0.036832
							149			3499.2	0.036832
150			6933.9	0.036832
							151			10082	0.038936
152			1661.8	0.038936
							153			6909.5	0.038936
154			6929.9	0.038936
							155			11633	0.041138
156			1938.3	0.041138
							157			2843.4	0.041138
158			1455.8	0.043443
							159			2440.7	0.043443

160			2683.7	0.043443
							161			3917.6	0.043443
162			75273	0.043443
							163			7655	0.043443
164			1189	0.045854
							165			1432.9	0.045854
166			1844.6	0.045854
							167			3461.1	0.045854
168			3465.6	0.045854
							169			3991.5	0.045854
170			1496.5	0.048373
							171			17459	0.048373
172			1861.2	0.048373
							173			6543.1	0.048373
174			6917.4	0.048373

Table 29

The SELDI biomarker p value of the feature different: WCX-2 chip with baseline

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	1273.2	0.000218	2342.5	0.000306	3582.0	7.09E-05
2	1827.7	0.000917	2340.9	0.000648	1855.2	0.000281
							3	1332.5	0.00325	1422.1	0.005797	5366.9	0.001064
4	1605.9	0.005962	1737.8	0.012367	1883.3	0.001659
							5	1773.1	0.006362	3178.5	0.013202	1888.2	0.002055
6	1158.8	0.007706	3776.7	0.013202	2469.2	0.002533
							7	4980.0	0.007706	1627.8	0.018149	1911.2	0.003436
8	4001.1	0.008207	1736.7	0.019309	2041.5	0.003436
							9	1147.4	0.009294	4001.1	0.02182	2041.8	0.003436
10	1095.9	0.009883	1860.4	0.023176	2042.1	0.003436
							11	6635.1	0.01116	1738.5	0.026105	1083.5	0.003795
12	1198.6	0.01185	1267.0	0.027683	1939.1	0.004187
							13	4407.6	0.01185	1793.8	0.027683	2042.4	0.004187
14	4408.0	0.01185	14975.	0.032909	4937.3	0.004187
							15	3582.0	0.012578	1523.5	0.032909	5399.9	0.004187
16	1606.5	0.013343	4796.8	0.032909	2011.7	0.004614
							17	1173.8	0.014149	2340.1	0.034824	1994.2	0.005078
18	1731.7	0.014149	1628.9	0.038936	2051.4	0.005078
							19	1213.0	0.014997	1875.7	0.041138	1371.1	0.006132
20	1605.1	0.014997	5347.5	0.043443	2045.1	0.006132
							21	1162.1	0.015888	1627.0	0.045854	1081.3	0.008827
22	1276.6	0.016824	3927.7	0.045854	1625.3	0.008827
							23	2109.1	0.016824			1155.3	0.009644

24	2754.9	0.016824			1793.8	0.009644
							25	1756.5	0.017807			2029.5	0.009644
26	1461.0	0.01884			1118.9	0.010525
							27	1525.2	0.01884			2048.7	0.010525
28	5366.9	0.01884			1940.2	0.011475
							29	1146.6	0.019923			1731.7	0.012498
30	1205.3	0.019923			1909.1	0.012498
							31	1523.5	0.019923			2015.1	0.012498
32	3238.3	0.019923			2062.3	0.012498
							33	1345.4	0.021059			4001.1	0.012498
34	3753.8	0.022249			4862.4	0.012498
							35	1315.0	0.023497			5347.5	0.012498
36	3641.1	0.023497			1779.1	0.014781
							37	8853.7	0.023497			1781.2	0.014781
38	1172.2	0.024804			2008.4	0.016052
							39	2538.5	0.024804			2039.2	0.016052
40	1347.7	0.026171			2116.7	0.016052
							41	2202.7	0.026171			1082.7	0.017414
42	1836.1	0.027603			1488.4	0.017414
							43	4406.3	0.027603			2885.9	0.017414
44	4466.0	0.027603			3485.1	0.018874
							45	1241.4	0.029099			7012.9	0.018874
46	1548.4	0.029099			1991.2	0.020437
							47	1724.7	0.029099			1315.0	0.025801
48	6780.5	0.029099			2070.5	0.025801
							49	1098.4	0.030664			2880.8	0.025801
50	3703.5	0.030664			1879.5	0.027834
							51	4465.4	0.032299			1084.8	0.030000
52	4467.7	0.032299			1879.2	0.030000
							53	11700.	0.034006			2059.5	0.030000
54	1462.6	0.034006			1867.4	0.032305
							55	3974.5	0.034006			2005.5	0.032305
56	1084.8	0.035789			1138.8	0.034756
							57	1089.0	0.035789			1523.5	0.034756
58	1215.0	0.035789			1879.7	0.034756
							59	1293.1	0.035789			2018.1	0.034756
60	1799.2	0.035789			1370.2	0.037360
							61	3094.3	0.035789			1878.3	0.037360
62	1320.0	0.037649			1293.1	0.040123
							63	1860.4	0.037649			1314.6	0.040123
64	1875.7	0.037649			2896.7	0.040123
							65	1460.1	0.039588			1232.9	0.043054
66	1747.4	0.039588			1878.8	0.043054
							67	2201.8	0.039588			1981.9	0.043054
68	2438.8	0.039588			1997.2	0.043054
							69	1172.8	0.041611			4589.5	0.043054
70	1220.5	0.041611			1172.8	0.046158
							71	2310.5	0.041611			1329.1	0.046158

72	2579.4	0.043718			1892.3	0.046158
							73	4774.0	0.043718			1086.3	0.049444
74	5106.3	0.045912			1111.4	0.049444
							75	1155.3	0.048197			14087.	0.049444
76	2055.8	0.048197			1626.1	0.049444
							77	6053.8	0.048197			4372.3	0.049444
78	8582.1	0.048197

Table 30

The SELDI biomarker p value of the feature different: WCX-2 chip with baseline

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	11484.	0.000874	11676.	0.001201	3067.9	0.017414
2	11463.	0.001116	5379.4	0.003717	3588.0	0.017414
							3	10509.	0.00242	11716.	0.004655	5006.0	0.020437
4	6864.8	0.002606	8354.6	0.008843	11484.	0.025801
							5	11413.	0.002805	8342.3	0.01013	5379.4	0.025801
6	9487.6	0.003244	8347.3	0.01013	11413.	0.027834
							7	11880.	0.003743	8384.2	0.01013	3173.1	0.027834
8	3738.5	0.004309	3496.6	0.010833	11591.	0.03736
							9	11343.	0.006491	8352.3	0.010833	1229.1	0.040123
10	11591.	0.009591	8360.4	0.010833	11463.	0.043054
							11	11525.	0.012314	11525.	0.01502	11716.	0.043054
12	11676.	0.012314	17387.	0.016007	5670.5	0.046158
							13	5277.2	0.012314	3639.3	0.016007	11525.	0.049444
14	10452.	0.013912	5858.1	0.016007
							15	11272.	0.014775	5849.2	0.017049
16	12006.	0.014775	5842.6	0.019309
							17	11641.	0.016642	8421.8	0.019309
18	11716.	0.016642	11413.	0.020532
							19	11635.	0.017649	1893.8	0.02182
20	11773.	0.017649	5866.0	0.024604
							21	12588.	0.017649	74907.	0.024604
22	14629.	0.017649	11484.	0.026105
							23	5873.3	0.019822	11641.	0.027683
24	11628.	0.020991	8454.3	0.027683
							25	31462.	0.022218	6484.4	0.029341
26	4122.3	0.023506	66578.	0.029341
							27	5906.8	0.024858	3588.0	0.031082
28	5910.4	0.024858	73096.	0.031082
							29	28210.	0.026274	1138.0	0.032909
30	3525.9	0.026274	11463.	0.034824

31	4964.9	0.026274	1069.6	0.036832
							32	5866.0	0.026274	3610.4	0.036832
33	5902.3	0.026274	1005.9	0.041138
							34	5858.1	0.027758	11591.	0.041138
35	5894.0	0.027758	11635.	0.045854
							36	5885.5	0.029312	11880.	0.045854
37	7059.4	0.029312	3279.6	0.045854
							38	1119.9	0.030939	4356.3	0.045854
39	4144.2	0.030939	5002.5	0.045854
							40	5286.1	0.030939	11343.	0.048373
41	5950.5	0.030939	3618.8	0.048373
							42	3777.4	0.032642	8471.9	0.048373
43	9809.4	0.034422
							44	4138.9	0.036282
45	7052.8	0.040256
							46	5878.5	0.042375
47	3369.2	0.044585
							48	7077.7	0.044585
49	4137.2	0.04689
							50	7318.4	0.04689
51	5842.6	0.049292
							52	5957.5	0.049292

Table 31

The SELDI biomarker p value of the feature different: WCX-2 chip with baseline

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	3681.1	0.001416	17459.	6.46E-05	16072	0.001659
2	37873.	0.001532	17749.	0.000371	11489.	0.002283
							3	8312.8	0.001532	8315.0	0.000926	1613.6	0.004187
4	11472.	0.001788	8312.8	0.001011	1882.6	0.004614
							5	54016.	0.00193	1877.3	0.001102	1665.2	0.006132
6	9126.4	0.00193	8504.1	0.001201	1833.4	0.007373
							7	9129.0	0.003244	1182.2	0.001308	1846.3	0.008071
8	11489.	0.004017	17253.	0.001681	2960.8	0.009644
							9	1665.2	0.004017	4580.0	0.001681	1565.9	0.010525
10	5855.0	0.004017	8327.3	0.001981	4921.6	0.010525
							11	14392.	0.004309	4125.5	0.003444	11661.	0.011475
12	9132.4	0.004309	8545.4	0.003444	1549.1	0.011475
							13	6007.8	0.00462	2173.6	0.003717	11648.	0.012498
14	8315.0	0.00462	11489.	0.004321	2073.0	0.013598
							15	3511.0	0.004951	1593.2	0.004321	2528.2	0.013598

16	11836.	0.005302	3871.9	0.004321	2307.2	0.014781
							17	1879.1	0.005302	8345.6	0.004655	11419.	0.016052
18	4573.6	0.006071	9155.0	0.005392	17459.	0.016052
							19	5830.6	0.006936	3036.4	0.005797	3146.8	0.016052
20	1176.9	0.007408	1633.6	0.006229	1585.3	0.017414
							21	1180.2	0.007909	3748.9	0.00669	11472.	0.020437
22	11398.	0.008438	1412.8	0.007179	11691.	0.020437
							23	5975.9	0.009591	3042.0	0.007179	1582.6	0.020437
24	11691.	0.010879	4573.6	0.007701	1880.7	0.020437
							25	5781.7	0.011577	8693.3	0.008843	3241.7	0.020437
26	11732.	0.012314	8398.7	0.009468	5198.9	0.020437
							27	19083.	0.012314	8770.5	0.01013	1180.2	0.023895
28	2782.2	0.012314	1154.3	0.010833	1537.9	0.023895
							29	1817.3	0.013092	3939.8	0.011578	2274.5	0.023895
30	5770.5	0.013092	1685.2	0.012367	2338.3	0.023895
							31	9091.2	0.013092	8789.0	0.012367	2671.1	0.023895
32	9108.6	0.013092	1234.5	0.01502	36974.	0.023895
							33	11964.	0.013912	2437.2	0.01502	1563.4	0.025801
34	11444.	0.014775	3442.4	0.01502	1612.1	0.025801
							35	2379.3	0.014775	4353.1	0.01502	1852.4	0.025801
36	5864.2	0.014775	8759.4	0.01502	1417.8	0.027834
							37	1412.8	0.015685	8781.0	0.01502	1616.6	0.027834
38	2953.5	0.015685	8874.0	0.01502	11532.	0.03
							39	5845.6	0.015685	11472.	0.016007	1576.9	0.03
40	8298.4	0.015685	1480.9	0.016007	20146.	0.03
							41	11661.	0.016642	1701.2	0.016007	3427.8	0.03
42	1385.0	0.016642	8421.7	0.016007	5837.4	0.032305
							43	3530.1	0.016642	2443.3	0.017049	1413.7	0.034756
44	9080.9	0.016642	11633.	0.018149	2335.2	0.034756
							45	11648.	0.018709	11691.	0.018149	2758.3	0.034756
46	11895.	0.018709	1460.3	0.018149	2935.4	0.034756
							47	1655.0	0.018709	8381.0	0.018149	3744.4	0.034756
48	9087.5	0.018709	11648.	0.019309	1162.6	0.03736
							49	1212.5	0.019822	1233.7	0.019309	1534.2	0.03736
50	5356.2	0.019822	2064.9	0.019309	1575.1	0.03736
							51	1690.2	0.020991	8815.8	0.019309	1584.3	0.03736
52	3980.6	0.020991	1097.0	0.020532	1602.7	0.03736
							53	4117.5	0.020991	11661.	0.02182	17749.	0.03736
54	5886.6	0.020991	9230.4	0.02182	1871.1	0.03736
							55	17749.	0.022218	9605.1	0.02182	2090.9	0.03736
56	2369.0	0.022218	11615.	0.023176	4580.0	0.03736
							57	4119.1	0.022218	8730.7	0.023176	5845.6	0.03736
58	3516.2	0.023506	1183.1	0.024604	5855.0	0.03736
							59	3894.7	0.024858	1416.4	0.024604	1712.0	0.040123
60	9155.0	0.024858	1455.8	0.024604	2066.8	0.040123
							61	11532.	0.026274	2440.7	0.024604	1562.6	0.043054
62	2437.2	0.026274	3973.5	0.024604	19909.	0.043054
							63	3490.7	0.026274	4697.7	0.024604	9466.5	0.043054

64	3710.4	0.026274	5215.7	0.024604	11895.	0.046158
							65	4120.8	0.026274	5464.9	0.024604	1605.5	0.046158
66	17459.	0.027758	5552.3	0.024604	3088.0	0.046158
							67	2683.7	0.027758	8298.4	0.024604	3095.6	0.046158
68	5872.8	0.027758	9687.7	0.024604	4710.2	0.046158
							69	11633.	0.029312	1477.6	0.026105	5215.7	0.046158
70	4155.9	0.029312	1478.3	0.026105	1510.2	0.049444
							71	11797.	0.030939	3439.0	0.026105	1522.8	0.049444
72	33911.	0.030939	11398.	0.027683	5607.0	0.049444
							73	5837.4	0.030939	1180.2	0.027683
74	9064.6	0.030939	1257.5	0.027683
							75	5228.6	0.032642	2170.5	0.027683
76	3893.0	0.034422	5837.4	0.027683
							77	11578.	0.036282	9004.4	0.027683
78	1897.2	0.036282	1009.4	0.029341
							79	2151.8	0.036282	11895.	0.029341
80	3744.4	0.036282	1414.9	0.029341
							81	4580.0	0.036282	1450.6	0.029341
82	5093.6	0.036282	2171.9	0.029341
							83	6851.5	0.036282	6192.3	0.029341
84	1160.8	0.038226	8791.2	0.029341
							85	33455.	0.038226	8840.8	0.029341
86	2686.8	0.040256	1051.4	0.031082
							87	3977.8	0.040256	1206.8	0.031082
88	5408.3	0.040256	1254.6	0.031082
							89	5998.1	0.040256	13423.	0.031082
90	7332.1	0.042375	1460.7	0.031082
							91	11766.	0.044585	16690.	0.031082
92	1666.5	0.044585	1686.4	0.031082
							93	1891.8	0.044585	5781.7	0.031082
94	3059.3	0.044585	11532.	0.032909
							95	3701.0	0.044585	1434.6	0.032909
96	11287.	0.049292	1457.3	0.032909
							97	11419.	0.049292	1690.2	0.032909
98	3109.4	0.049292	2553.8	0.032909
							99			3522.5	0.032909
100			3605.1	0.032909
							101			5855.0	0.032909
102			8847.4	0.032909
							103			1181.3	0.034824
104			1454.4	0.034824
							105			1479.5	0.034824
106			16980.	0.034824
							107			3062.6	0.034824
108			3924.2	0.034824
							109			3933.6	0.034824
110			1253.9	0.036832
							111			1463.1	0.036832

112			1482.1	0.036832
							113			1595.8	0.036832
114			3945.3	0.036832
							115			5722.6	0.036832
116			11444.	0.038936
							117			3331.3	0.038936
118			3929.1	0.038936
							119			5607.0	0.038936
120			2180.0	0.041138
							121			4615.2	0.041138
122			4636.3	0.041138
							123			5845.6	0.041138
124			1772.5	0.043443
							125			3688.4	0.043443
126			5408.3	0.043443
							127			1050.8	0.045854
128			1051.7	0.045854
							129			1081.5	0.045854
130			11419.	0.045854
							131			1188.4	0.045854
132			12839.	0.045854
							133			1925.8	0.045854
134			3362.0	0.045854
							135			5770.5	0.045854
136			5830.6	0.045854
							137			1938.3	0.048373
138			2196.2	0.048373
							139			3095.6	0.048373
140			4336.2	0.048373
							141			9132.4	0.048373

Table 32

SELDI biomarker p value: H50 chip

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	6694.1	0.000104	3892.3	0.000371	3683.8	0.014882
2	8934.6	0.00037	3458.7	0.000492	4288.3	0.014882
							3	9141.2	0.000519	1057	0.00054	4290.5	0.014882
4	8223.8	0.000782	1015.1	0.000648	4471.7	0.014882
							5	1298.9	0.001253	5836.1	0.000709	1690.8	0.01598
6	9297.4	0.001353	1315.8	0.000776	12872	0.017146
							7	28047	0.002277	28768	0.000776	4289	0.018385

8	4005.1	0.00325	9141.2	0.001102	6694.1	0.018385
							9	6442.9	0.00325	5837.6	0.001201	6442.9	0.024132
10	6639.4	0.003483	1033.9	0.001308	3220	0.029382
							11	1341.4	0.004278	6639.4	0.001308	6639.4	0.031332
12	1448.5	0.004278	1314.3	0.001423	1748.9	0.03339
							13	4719.4	0.004278	5839.4	0.001547	1178.1	0.035559
14	1340.6	0.004893	4418.6	0.001681	9141.2	0.042783
							15	28768	0.005229	1034.1	0.001826	8934.6	0.045445
16	1461.8	0.005585	18741	0.001826	4645.9	0.048242
							17	9341.7	0.005585	28047	0.001826
18	3867.5	0.006785	7300.1	0.001826
							19	1456.7	0.007706	2699.3	0.001981
20	8799.9	0.007706	1000.2	0.002148
							21	4471.7	0.009883	1033.7	0.002148
22	1706.1	0.010504	1313	0.002328
							23	4109.5	0.010504	14049	0.002328
24	2959.1	0.012578	5840.9	0.002328
							25	4116.2	0.012578	9479.1	0.002328
26	3220	0.013343	14500	0.002521
							27	3345.3	0.013343	9376.8	0.002521
28	1692.9	0.014149	3942.2	0.002728
							29	6898.8	0.014997	5813.3	0.002728
30	4290.5	0.016824	1032.3	0.003188
							31	12872	0.017807	4467	0.003188
32	14049	0.01884	6442.9	0.003188
							33	1026.3	0.019923	9297.4	0.003188
34	4442	0.019923	1014	0.003444
							35	4467	0.021059	3206.4	0.003444
36	3913.4	0.022249	1016.3	0.003717
							37	4580.6	0.023497	1313.6	0.003717
38	1339.2	0.024804	1245	0.004009
							39	1422.4	0.024804	1043.5	0.004321
40	2794.8	0.024804	1001	0.005011
							41	2932.7	0.026171	1142.4	0.005011
42	4289	0.026171	1318	0.005011
							43	1088.9	0.027603	3896.1	0.005011
44	18741	0.027603	4471.7	0.005392
							45	2301	0.027603	6694.1	0.005392
46	3919.9	0.027603	1009.1	0.005797
							47	4675.5	0.027603	1246.5	0.006229
48	7846.5	0.027603	2712.8	0.006229
							49	9376.8	0.029099	8934.6	0.006229
50	1342.1	0.030664	1002.6	0.00669
							51	1427.9	0.030664	1127.9	0.007179
52	14500	0.030664	1249	0.007179
							53	1014	0.032299	1706.1	0.007179
54	4288.3	0.032299	8799.9	0.007179
							55	4426.9	0.032299	1158.5	0.007701

56	1341.8	0.034006	1304.5	0.007701
							57	2940.7	0.034006	3329.6	0.007701
58	1297.4	0.035789	3889.9	0.007701
							59	1433.3	0.035789	1027.7	0.008254
60	4458	0.035789	14300	0.008254
							61	7009.7	0.035789	9341.7	0.008254
62	3322.1	0.037649	1129.5	0.008843
							63	7035.6	0.039588	1285.4	0.008843
64	2992.1	0.041611	12872	0.008843
							65	3942.2	0.041611	1319.2	0.008843
66	1690.8	0.045912	1328	0.008843
							67	4486.8	0.045912	3888.9	0.008843
68			5830.2	0.008843
							69			5844.8	0.008843
70			1312.1	0.009468
							71			3840.3	0.009468
72			4116.2	0.009468
							73			1012	0.01013
74			1029.6	0.01013
							75			1054.8	0.01013
76			1007.9	0.011578
							77			1027.1	0.011578
78			2907.4	0.011578
							79			6090.8	0.011578
80			3232.1	0.012367
							81			1010.4	0.013202
82			1113	0.013202
							83			1301.8	0.013202
84			5798.6	0.013202
							85			1250.5	0.014086
86			1286.1	0.014086
							87			1286.7	0.014086
88			2910.2	0.014086
							89			4426.9	0.014086
90			4479.1	0.014086
							91			9684.3	0.014086
92			11626	0.01502
							93			3879.9	0.01502
94			5759.1	0.01502
							95			1012.9	0.016007
96			11594	0.016007
							97			4442	0.016007
98			4694.2	0.016007
							99			1004.9	0.017049
100			1006.9	0.017049
							101			1011.1	0.017049
102			1055.1	0.017049
							103			1287.1	0.017049

104			1298.9	0.017049
							105			2211.2	0.017049
106			2916.5	0.017049
							107			2922.9	0.017049
108			3886.3	0.017049
							109			7846.5	0.017049
110			1028	0.018149
							111			1233.7	0.018149
112			2729.8	0.018149
							113			3844.1	0.018149
114			1263.6	0.019309
							115			2902.8	0.019309
116			3905.9	0.019309
							117			3919.9	0.019309
118			7035.6	0.019309
							119			1020.5	0.020532
120			11685	0.020532
							121			1270.2	0.020532
122			1287.8	0.020532
							123			4580.6	0.020532
124			4303.4	0.02182
							125			4458	0.02182
126			12184	0.023176
							127			1287.4	0.023176
128			4290.5	0.023176
							129			4645.9	0.023176
130			4675.5	0.023176
							131			1113.6	0.024604
132			1114.7	0.024604
							133			1289.7	0.024604
134			3838.6	0.024604
							135			4719.4	0.024604
136			8223.8	0.024604
							137			1159.4	0.026105
138			11642	0.026105
							139			3810.5	0.026105
140			1128.6	0.027683
							141			1275	0.027683
142			1275.6	0.027683
							143			1361	0.027683
144			15122	0.027683
							145			3867.5	0.027683
146			5756.1	0.027683
							147			2119.1	0.029341
148			3225.5	0.029341
							149			1018.3	0.031082
150			1160.1	0.031082
							151			2036.2	0.031082

152			3345.3	0.031082
							153			5753.7	0.031082
154			1296.6	0.032909
							155			3149.5	0.032909
156			4464.1	0.032909
							157			7141.1	0.032909
158			1128.2	0.034824
							159			1296.4	0.034824
160			1344	0.034824
							161			3770.9	0.034824
162			3913.4	0.034824
							163			4486.8	0.034824
164			4682.5	0.034824
							165			5851.1	0.034824
166			5871.1	0.034824
							167			2003.2	0.036832
168			2932.7	0.036832
							169			3335.3	0.036832
170			1131.9	0.038936
							171			3242.6	0.038936
172			1062.4	0.041138
							173			1319.6	0.041138
174			2883.5	0.041138
							175			2940.7	0.041138
176			1112.3	0.043443
							177			1945.9	0.043443
178			5959.8	0.043443
							179			1019.6	0.045854
180			2018.3	0.045854
							181			1296.91	0.048373
182			3899.5	0.048373
							183			4288.3	0.048373
184			4385.7	0.048373
							185			5764.6	0.048373

Table 33

SELDI biomarker p value: H50 chip

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	43045	0.00325	3355.6	1.42E-06	9482	0.00759
2	42800	0.005962	4655.1	0.000277	6896.3	0.008861
							3	9482	0.007233	4508.5	0.000306	12870	0.01197
4	6896.3	0.014997	4724.4	0.000592	3048.4	0.031332
							5	42693	0.016824	4505.8	0.000648	43634	0.031332
6	10802	0.017807	4759.6	0.000648	10802	0.040251
							7	2949.6	0.019923	4680.3	0.000709	3233.2	0.042783
8	34925	0.021059	4516	0.000776	6493.9	0.048242
							9	6493.9	0.021059	4873	0.001102
10	8284	0.021059	4836.6	0.001308
							11	3552.8	0.022249	9034.2	0.001308
12	10465	0.026171	6127.7	0.001547
							13	73120	0.027603	11773	0.001826
14	10297	0.035789	9259.8	0.001826
							15	12870	0.035789	4851.1	0.001981
16	3813.5	0.035789	6096.4	0.001981
							17	14505	0.037649	3813.5	0.002328
18	6559.8	0.041611	4146	0.002328
							19	7119.7	0.041611	6109.4	0.002328
20	9158.7	0.043718	6087	0.002521
							21	5942.1	0.048197	6942.8	0.002521
22			11954	0.002728
							23			7143.1	0.002728
24			6778	0.003444
							25			7938.5	0.003444
26			4547	0.003717
							27			9669.7	0.003717
28			4692.2	0.004321
							29			4825.6	0.004321
30			6807.4	0.004321
							31			4157.7	0.004655
32			4532.8	0.004655
							33			13764	0.005392
34			4522.7	0.005392
							35			5868.8	0.005392
36			6493.9	0.005392
							37			6514.7	0.005392
38			9386.5	0.005392
							39			99801	0.005392

40			3469.4	0.005797
							41			6498.6	0.005797
42			6499.9	0.006229
							43			6501.7	0.006229
44			6505.1	0.006229
							45			4611.5	0.00669
46			6202.5	0.00669
							47			6533.4	0.00669
48			7083.7	0.00669
							49			7254.9	0.00669
50			12176	0.007179
							51			4141.6	0.007179
52			4701.7	0.007179
							53			6150.3	0.007701
54			6218.5	0.007701
							55			6896.3	0.007701
56			8296	0.007701
							57			9158.7	0.007701
58			4633.2	0.008843
							59			8284	0.008843
60			5889.9	0.01013
							61			6184.5	0.01013
62			8320.8	0.01013
							63			37619	0.010833
64			8293	0.010833
							65			5251.9	0.011578
66			5970.5	0.011578
							67			6685.4	0.011578
68			63590	0.012367
							69			6559.8	0.012367
70			7000.7	0.012367
							71			5893.5	0.013202
72			4481.1	0.01502
							73			6082.1	0.01502
74			6246.4	0.01502
							75			4892	0.016007
76			5905.7	0.016007
							77			5906.5	0.016007
78			6077.2	0.016007
							79			6275.7	0.016007
80			8297.6	0.016007
							81			12499	0.017049
82			5907.1	0.017049
							83			7119.7	0.017049
84			3969.4	0.018149
							85			9482	0.018149
86			3509.1	0.019309
							87			4792.7	0.019309

88			5226	0.019309
							89			5903.8	0.019309
90			5942.1	0.019309
							91			6166.2	0.019309
92			5898.8	0.020532
							93			5910	0.020532
94			24366	0.02182
							95			3934.7	0.02182
96			4142.9	0.02182
							97			4808.4	0.023176
98			22915	0.026105
							99			3383.3	0.026105
100			3951.8	0.027683
							101			11652	0.029341
102			3626.4	0.029341
							103			3826.7	0.029341
104			5923	0.029341
							105			6001.4	0.029341
106			12280	0.031082
							107			75442	0.031082
108			9759.4	0.031082
							109			1230.7	0.032909
110			5204.1	0.032909
							111			5279	0.032909
112			6157.8	0.032909
							113			1238.1	0.034824
114			11131	0.036832
							115			1263.4	0.036832
116			6068.9	0.036832
							117			23732	0.038936
118			4420.6	0.038936
							119			4454.7	0.038936
120			4917.8	0.038936
							121			11399	0.041138
122			4433.8	0.041138
							123			6033.3	0.041138
124			8931.7	0.041138
							125			69817	0.043443
126			11526	0.045854
							127			1290.2	0.045854
128			40894	0.045854
							129			8377.5	0.045854

Table 34

SELDI biomarker p value: H50 chip

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	9170.7	0.000151	1256.6	4.38E-06	2088.9	0.003637
2	9474.9	0.000285	1276.4	1.09E-05	9170.7	0.003637
							3	3024.3	0.00037	1227.8	1.24E-05	9474.9	0.005982
4	3030	0.000564	1255.5	1.41E-05	1965.4	0.009563
							5	1734.9	0.00116	1225.5	3.67E-05	6563.9	0.009563
6	9636.5	0.001253	1281.4	4.61E.05	12901	0.017146
							7	9420.3	0.001574	1275.4	5.17E-05	1956.6	0.017146
8	1716.9	0.001968	3336.5	5.17E-05	7282.6	0.021093
							9	9584.5	0.00303	1278	5.78E-05	2838.1	0.024132
10	3041.9	0.003483	2615.5	7.21E-05	1100.7	0.025786
							11	35268	0.003997	1229.1	8.04E-05	1132	0.027535
12	3019.4	0.004576	1283.2	8.04E-05	3024.3	0.027535
							13	6462.8	0.004576	1259.3	8.96E-05	1154.9	0.029382
14	6563.9	0.004576	1271.3	0.000137	1227.8	0.029382
							15	2781.2	0.004893	1281	0.000137	1680.3	0.029382
16	2019.2	0.005229	1281.9	0.000137	2942.9	0.029382
							17	4433.9	0.005962	1274.1	0.000152	6462.8	0.029382
18	12901	0.006785	12386	0.000186	1671.3	0.031332
							19	2010.8	0.006785	5943.2	0.000186	19918	0.03339
20	2997	0.007706	1272.6	0.000206	1101.1	0.035559
							21	5423.5	0.007706	1262.5	0.000228	1688.6	0.035559
22	4115.8	0.009294	1270.3	0.000228	2668.7	0.035559
							23	3007.3	0.01185	1299	0.000228	1100.3	0.037845
24	3550.5	0.01185	3335.8	0.000277	6660.6	0.037845
							25	3568.8	0.01185	6251.8	0.000277	2862	0.040251
26	3013.4	0.013343	6889	0.000277	1229.1	0.045445
							27	3332.4	0.014997	1284.5	0.000306	9300.5	0.045445
28	9334	0.014997	3342	0.000306	2680.7	0.048242
							29	3540.2	0.015888	1279.6	0.000337	3567.8	0.048242
30	10130	0.016824	1286.2	0.000337
							31	19918	0.016824	1258.6	0.000371
32	3813.9	0.016824	1260.6	0.000408
							33	9075.3	0.016824	1236	0.000448
34	9300.5	0.016824	1254.3	0.000448
							35	7282.6	0.017807	3335	0.000448
36	1985.3	0.019923	6187.5	0.000448
							37	28070	0.019923	1251.2	0.000492
38	3037.2	0.021059	1269.2	0.00054
							39	42896	0.021059	4832.1	0.00054

40	6660.6	0.021059	1253.1	0.000592
							41	8353.7	0.021059	1261.7	0.000592
42	1729.8	0.022249	1265.3	0.000592
							43	4744.2	0.022249	1280.4	0.000592
44	4886.7	0.022249	1219.8	0.000648
							45	2657	0.023497	1267.2	0.000648
46	7109.4	0.023497	3332.4	0.000648
							47	3944.1	0.024804	1263.6	0.000709
48	1281.4	0.026171	6087.5	0.000709
							49	14780	0.026171	12175	0.000776
50	9371.9	0.026171	1243.4	0.000776
							51	3880.5	0.027603	1258	0.000776
52	4536.2	0.027603	11626	0.000848
							53	3688.2	0.029099	1285.4	0.000848
54	1281.9	0.030664	12088	0.000926
							55	2024.7	0.032299	1301.2	0.000926
56	28759	0.032299	2442.4	0.000926
							57	28825	0.032299	1290.8	0.001011
58	3050.7	0.032299	1296.9	0.001011
							59	4446.4	0.032299	4593.6	0.001011
60	1281	0.034006	1294.7	0.001102
							61	2287.8	0.034006	1295.1	0.001102
62	2502.7	0.034006	4141.7	0.001102
							63	3962.3	0.034006	11932	0.001201
64	14194	0.035789	1287.5	0.001201
							65	1731.3	0.035789	6168	0.001201
66	2757.5	0.035789	6386.4	0.001201
							67	28777	0.035789	12031	0.001308
68	1117.7	0.039588	1294.3	0.001308
							69	2862	0.039588	1298.5	0.001308
70	1326.5	0.041611	1245.3	0.001547
							71	14111	0.041611	1289.2	0.001547
72	2260.5	0.041611	1252.6	0.001681
							73	4320.3	0.041611	4115.8	0.001681
74	1733.2	0.043718	6209.2	0.001681
							75	2278.6	0.043718	8982.8	0.001681
76	28307	0.043718	4697.2	0.001826
							77	4164.9	0.043718	1241.2	0.001981
78	14510	0.045912	1264.4	0.001981
							79	1710	0.048197	3557.3	0.001981
80			12271	0.002148
							81			1778.8	0.002148
82			4811	0.002148
							83			5960.9	0.002148
84			2423.7	0.002328
							85			1209.6	0.002728
86			1234	0.002728
							87			1293.7	0.002728

88			1300	0.002728
							89			1323.1	0.002728
90			3041.9	0.002728
							91			1239.7	0.00295
92			1241.9	0.00295
							93			4591.4	0.00295
94			4846.2	0.00295
							95			9474.9	0.00295
96			9300.5	0.003188
							97			12508	0.003444
98			1325.3	0.003444
							99			6096	0.003444
100			1295.7	0.003717
							101			1302.6	0.003717
102			5825.1	0.004009
							103			6109.3	0.004321
104			1292.6	0.004655
							105			1298	0.004655
106			1249.3	0.005011
							107			1309.4	0.005011
108			1774.7	0.005392
							109			2408.4	0.005392
110			5072.1	0.005392
							111			1237.5	0.005797
112			1689.8	0.005797
							113			2413.8	0.005797
114			4744.2	0.005797
							115			11779	0.006229
116			4499.6	0.006229
							117			1800.6	0.00669
118			8865.2	0.00669
							119			10273	0.007179
120			7109.4	0.007179
							121			90753	0.007179
122			9170.7	0.007179
							123			9334	0.007179
124			1324.3	0.008254
							125			5843.1	0.008254
126			1330.1	0.008843
							127			9636.5	0.008843
128			1311.6	0.009468
							129			9706.4	0.009468
130			1331	0.01013
							131			1782.7	0.01013
132			23767	0.01013
							133			2421.1	0.01013
134			4860.2	0.01013
							135			1312.8	0.010833

136			2816.8	0.010833
							137			2889.3	0.010833
138			1109	0.011578
							139			1306.8	0.011578
140			14111	0.011578
							141			4613.5	0.011578
142			4876	0.011578
							143			11351	0.012367
144			2082.2	0.012367
							145			4540.2	0.012367
146			4796.5	0.012367
							147			9420.3	0.012367
148			1230.7	0.013202
							149			1307.9	0.013202
150			1105.7	0.014086
							151			1226.6	0.014086
152			1303.6	0.014086
							153			1309.8	0.014086
154			1326.5	0.014086
							155			2403.2	0.014086
156			1304.8	0.01502
							157			2434.1	0.01502
158			4994.4	0.01502
							159			1104	0.016007
160			1310	0.016007
							161			3019.4	0.016007
162			37418	0.016007
							163			5241.4	0.016007
164			6660.6	0.016007
							165			9371.9	0.016007
166			11519	0.017049
							167			1310.5	0.017049
168			46718	0.017049
							169			4886.7	0.017049
170			5855.8	0.017049
							171			1315.6	0.018149
172			1332.2	0.018149
							173			3215.9	0.018149
174			9930.7	0.018149
							175			11687	0.019309
176			1223.8	0.019309
							177			1314.3	0.019309
178			2849.9	0.019309
							179			3348.6	0.019309
180			1321.8	0.020532
							181			4767.8	0.020532
182			4968.8	0.020532
							183			6139.2	0.020532

184			8497	0.020532
							185			2580.5	0.02182
186			33454	0.02182
							187			3438.9	0.02182
188			3449.4	0.02182
							189			6462.8	0.02182
190			9764	0.02182
							191			1117	0.023176
192			1218.7	0.023176
							193			1222.6	0.023176
194			1240.9	0.023176
							195			5867.8	0.023176
196			5906.9	0.023176
							197			1154.9	0.024604
198			1320.4	0.024604
							199			2024.7	0.024604
200			1234.8	0.026105
							201			1713.9	0.026105
202			1780.9	0.026105
							203			1837.8	0.026105
204			4713.3	0.026105
							205			4873.9	0.026105
206			5698.7	0.026105
							207			9584.5	0.026105
208			1058.2	0.027683
							209			1120.4	0.027683
210			1321	0.027683
							211			2685.4	0.027683
212			1107.5	0.029341
							213			1121.4	0.029341
214			1221	0.029341
							215			1224.5	0.029341
216			1621.1	0.029341
							217			2686.7	0.029341
218			4555.1	0.029341
							219			6047.3	0.029341
220			1231.9	0.031082
							221			23126	0.031082
222			23145	0.031082
							223			3962.3	0.031082
224			1059.5	0.032909
							225			1308.7	0.032909
226			1317.2	0.032909
							227			1328.1	0.032909
228			4628.7	0.032909
							229			1067.1	0.034824
230			1428.2	0.034824
							231			1060.8	0.036832

232			11132	0.036832
							233			11550	0.036832
234			1215	0.036832
							235			1216.3	0.036832
236			23106	0.036832
							237			2404	0.036832
238			5075.4	0.036832
							239			5171.3	0.036832
240			1071	0.038936
							241			1798.8	0.038936
242			4433.9	0.038936
							243			45039	0.038936
244			1057.1	0.041138
							245			1086.5	0.041138
246			1211.6	0.041138
							247			1217.7	0.041138
248			1238.5	0.041138
							249			28307	0.041138
250			3217.8	0.041138
							251			3313.1	0.041138
252			4446.4	0.041138
							253			1110.4	0.043443
254			1427.6	0.043443
							255			2104.6	0.043443
256			2679	0.043443
							257			1011.8	0.045854
258			1085.8	0.045854
							259			11537	0.045854
260			23420	0.045854
							261			28070	0.045854
262			2826.3	0.045854
							263			4603.1	0.045854
264			1100.3	0.048373
							265			1115.1	0.048373
266			23251	0.048373
							267			40679	0.048373
268			4371.1	0.048373
							269			4526.6	0.048373
270			8743.7	0.048373
							271			8937.9	0.048373

Table 35

The SELDI biomarker p value of the feature different: H50 chip with baseline

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	3888.9	3.46E-05	1706.1	2.58E-05	12872	2.81E-03
2	3883.4	3.84E-05	3892.3	4.12E-05	3798.2	4.61E-03
							3	3889.9	4.71E-05	3942.2	6.46E-05	2910.2	6.13E-03
4	18741	7.03E-05	18741	8.04E-05	3801.5	6.73E-03
							5	3886.3	1.25E-04	5836.1	8.96E-05	6898.8	6.73E-03
6	2875.9	1.38E-04	5813.3	9.97E-05	1706.1	8.83E-03
							7	28047	1.51E-04	3889.9	1.37E-04	3810.5	8.83E-03
8	2925.5	3.39E-04	5837.6	1.52E-04	1070.8	9.64E-03
							9	5709.8	3.39E-04	3888.9	2.06E-04	5696.5	9.64E-03
10	3899.5	4.03E-04	5839.4	2.28E-04	5709.8	1.15E-02
							11	14049	5.64E-04	5830.2	3.37E-04	1286.1	1.61E-02
12	1289.7	7.21E-04	5844.8	4.48E-04	2288.7	1.61E-02
							13	3867.5	7.21E-04	3840.3	4.92E-04	5557.5	1.61E-02
14	11125	8.47E-04	3458.7	5.40E-04	18741	1.89E-02
							15	5666.2	8.47E-04	5840.9	5.92E-04	3805	2.21E-02
16	3849.3	9.17E-04	3883.4	6.48E-04	3847.4	2.39E-02
							17	3892.3	9.17E-04	5759.1	6.48E-04	3879.9	2.58E-02
18	4675.5	9.17E-04	11594	7.76E-04	3883.4	2.58E-02
							19	2922.9	9.92E-04	11626	7.76E-04	4289	2.58E-02
20	3840.3	9.92E-04	12872	9.26E-04	2269.6	2.78E-02
							21	5557.5	9.92E-04	5798.6	1.10E-03	2922.9	2.78E-02
22	5830.2	9.92E-04	11685	1.20E-03	1070.2	3.00E-02
							23	1706.1	1.07E-03	11642	1.31E-03	3835.3	3.00E-02
24	3850.1	1.07E-03	14049	1.31E-03	3867.5	3.00E-02
							25	3919.9	1.07E-03	5756.1	1.42E-03	3888.9	3.00E-02
26	8223.8	1.07E-03	5851.1	1.68E-03	4288.3	3.00E-02
							27	28768	1.16E-03	15122	1.83E-03	4385.7	3.00E-02
28	3805	1.25E-03	3879.9	1.83E-03	3848.4	3.23E-02
							29	3810.5	1.25E-03	5753.7	1.83E-03	3899.5	3.23E-02
30	3913.4	1.25E-03	1315.8	1.98E-03	5871.1	3.23E-02
							31	6898.8	1.35E-03	3838.6	1.98E-03	8223.8	3.23E-02
32	3848.4	1.46E-03	3886.3	2.15E-03	5813.3	3.48E-02
							33	3816.4	1.57E-03	2907.4	2.33E-03	1223.9	3.74E-02
34	3942.2	1.57E-03	3905.9	2.33E-03	15122	3.74E-02
							35	3798.2	1.70E-03	2910.2	2.52E-03	2729.8	3.74E-02
36	3830	1.70E-03	28047	2.73E-03	2929.8	3.74E-02
							37	3905.9	1.70E-03	3810.5	2.95E-03	3901.4	3.74E-02
38	3879.9	1.83E-03	3835.3	2.95E-03	3849.3	4.31E-02
							39	3903.5	1.97E-03	3896.1	2.95E-03	3861.3	4.31E-02

40	3853	2.12E-03	3919.9	2.95E-03	4109.5	4.31E-02
							41	25836	2.28E-03	5764.6	3.19E-03	5156.6	4.31E-02
42	3901.4	2.28E-03	5854.7	3.19E-03	5798.6	4.62E-02
							43	4486.8	2.28E-03	11453	3.44E-03	14500	4.94E-02
44	3847.4	2.45E-03	14500	3.44E-03	2902.8	4.94E-02
							45	3902.6	2.45E-03	11484	3.72E-03	2907.4	4.94E-02
46	3832.1	2.63E-03	1246.5	4.01E-03	3840.3	4.94E-02
							47	5836.1	2.63E-03	2916.5	4.01E-03	3850.1	4.94E-02
48	5749.7	2.82E-03	3867.5	4.01E-03	3919.9	4.94E-02
							49	6694.1	2.82E-03	9376.8	4.32E-03	4303.4	4.94E-02
50	3820.1	3.03E-03	5749.7	4.66E-03
							51	5753.7	3.03E-03	9479.1	4.66E-03
52	4479.1	3.25E-03	2932.7	5.01E-03
							53	5756.1	3.48E-03	1289.7	5.39E-03
54	5837.6	3.48E-03	3225.5	5.39E-03
							55	5744.9	3.73E-03	3232.1	5.39E-03
56	3838.6	4.00E-03	3899.5	5.39E-03
							57	5724	4.00E-03	14300	5.80E-03
58	3225.5	4.28E-03	3844.1	5.80E-03
							59	3823.1	4.28E-03	18184	6.23E-03
60	3835.3	4.28E-03	2875.9	6.23E-03
							61	4005.1	4.28E-03	2883.5	6.69E-03
62	12872	4.58E-03	3801.5	7.18E-03
							63	14300	4.58E-03	5724	7.18E-03
64	3826.2	4.58E-03	11508	7.70E-03
							65	5773.1	4.58E-03	5744.9	7.70E-03
66	5851.1	4.58E-03	8934.6	7.70E-03
							67	3801.5	4.89E-03	3798.2	8.25E-03
68	11484	5.23E-03	3901.4	8.25E-03
							69	11642	5.23E-03	5770.7	8.25E-03
70	5813.3	5.23E-03	11402	8.84E-03
							71	2927.5	5.58E-03	5857.1	8.84E-03
72	5733.6	5.58E-03	7846.5	9.47E-03
							73	8934.6	5.58E-03	12184	1.01E-02
74	5730.9	5.96E-03	5696.5	1.01E-02
							75	5774.3	5.96E-03	7141.1	1.01E-02
76	5798.6	5.96E-03	1142.4	1.08E-02
							77	9376.8	5.96E-03	28768	1.08E-02
78	11453	6.36E-03	3902.6	1.08E-02
							79	5770.7	6.36E-03	3903.5	1.16E-02
80	11626	6.78E-03	8223.8	1.16E-02
							81	2959.1	6.78E-03	2929.8	1.24E-02
82	4719.4	6.78E-03	3329.6	1.24E-02
							83	5728	6.78E-03	3805	1.24E-02
84	5844.8	6.78E-03	5709.8	1.24E-02
							85	11685	7.23E-03	7035.6	1.32E-02
86	9479.1	7.23E-03	9684.3	1.32E-02
							87	2864.2	7.71E-03	2109.6	1.41E-02

88	2932.7	7.71E-03	4479.1	1.41E-02
							89	5585.1	7.71E-03	5156.6	1.41E-02
90	5759.1	7.71E-03	3847.4	1.50E-02
							91	1112.3	8.21E-03	5734.4	1.50E-02
92	15122	8.21E-03	5773.1	1.50E-02
							93	3844.1	8.21E-03	5871.1	1.50E-02
94	5696.5	8.21E-03	1304.5	1.60E-02
							95	5734.4	8.21E-03	3913.4	1.60E-02
96	5839.4	8.21E-03	5791.4	1.70E-02
							97	5840.9	8.21E-03	6442.9	1.70E-02
98	11594	8.74E-03	7300.1	1.70E-02
							99	2902.8	8.74E-03	9297.4	1.70E-02
100	5959.8	8.74E-03	2922.9	1.81E-02
							101	3857.6	9.88E-03	3820.1	1.81E-02
102	5854.7	9.88E-03	5666.2	1.81E-02
							103	4426.9	1.05E-02	1318	1.93E-02
104	5871.1	1.05E-02	3816.4	1.93E-02
							105	1298.9	1.12E-02	3830	1.93E-02
106	3821.5	1.12E-02	3848.4	1.93E-02
							107	9141.2	1.12E-02	3909.9	1.93E-02
108	2679.5	1.19E-02	5730.9	1.93E-02
							109	11402	1.26E-02	1245	2.05E-02
110	1328	1.26E-02	2196	2.18E-02
							111	2929.8	1.26E-02	3826.2	2.18E-02
112	5739.1	1.26E-02	4426.9	2.18E-02
							113	1315.8	1.33E-02	5728	2.18E-02
114	14500	1.33E-02	5733.6	2.18E-02
							115	3724.5	1.33E-02	11125	2.32E-02
116	5778.6	1.33E-02	3849.3	2.32E-02
							117	3093.8	1.41E-02	4694.2	2.32E-02
118	3683.8	1.41E-02	5739.1	2.32E-02
							119	3896.1	1.41E-02	5778.6	2.32E-02
120	6442.9	1.41E-02	2925.5	2.46E-02
							121	18184	1.50E-02	5774.3	2.46E-02
122	2301	1.50E-02	1015.1	2.61E-02
							123	2828.8	1.59E-02	1328	2.61E-02
124	5764.6	1.59E-02	2927.5	2.61E-02
							125	1246.5	1.78E-02	3832.1	2.61E-02
126	1775.7	1.78E-02	5786.5	2.61E-02
							127	11508	1.88E-02	5959.8	2.61E-02
128	5156.6	1.88E-02	3823.1	2.77E-02
							129	3861.3	1.99E-02	17385	2.93E-02
130	1319.2	2.11E-02	19852	2.93E-02
							131	1448.5	2.11E-02	2940.7	3.11E-02
132	2021.1	2.35E-02	6898.8	3.11E-02
							133	8799.9	2.48E-02	1016.3	3.29E-02
134	3909.9	2.76E-02	17262	3.29E-02
							135	4458	2.91E-02	2902.8	3.29E-02

136	4467	2.91E-02	3322.1	3.29E-02
							137	1342.1	3.07E-02	4303.4	3.29E-02
138	7035.6	3.07E-02	3093.8	3.48E-02
							139	9341.7	3.07E-02	6090.8	3.48E-02
140	1343.1	3.23E-02	9141.2	3.48E-02
							141	9297.4	3.23E-02	1104.4	3.68E-02
142	12184	3.40E-02	1263.6	3.68E-02
							143	1278.3	3.40E-02	1301.8	3.68E-02
144	2883.5	3.40E-02	3821.5	3.68E-02
							145	2916.5	3.40E-02	4471.7	3.68E-02
146	2794.8	3.58E-02	2864.2	3.89E-02
							147	1954.9	3.76E-02	1314.3	4.34E-02
148	3458.7	3.76E-02	1319.2	4.34E-02
							149	1286.1	3.96E-02	3683.8	4.34E-02
150	1812.9	3.96E-02	3850.1	4.34E-02
							151	2940.7	3.96E-02	1250.5	4.59E-02
152	4303.4	3.96E-02	1313	4.59E-02
							153	4471.7	4.16E-02	3853	4.59E-02
154	6639.4	4.16E-02	1007.9	4.84E-02
							155	1292.2	4.37E-02	8644.4	4.84E-02
156	5857.1	4.37E-02
							157	1314.3	4.59E-02
158	1318	4.59E-02
							159	2851.1	4.59E-02
160	4109.5	4.59E-02
							161	5786.5	4.59E-02
162	7009.7	4.59E-02
							163	1312.1	4.82E-02
164	17385	4.82E-02
							165	4580.6	4.82E-02
166	5791.4	4.82E-02

Table 36

The SELDI biomarker p value of the feature different: H50 chip with baseline

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	6493.9	5.64E-04	3355.6	1.23E-04	12870	1.49E-03
2	14505	1.07E-03	6001.4	3.37E-04	6275.7	3.44E-03
							3	3436.7	2.12E-03	5898.8	4.08E-04	5596.1	4.19E-03
4	12870	3.73E-03	5970.5	4.08E-04	6246.4	4.19E-03
							5	6896.3	4.89E-03	5889.9	5.40E-04	19997	4.61E-03

6	14607	5.23E-03	5893.5	5.40E-04	6184.5	5.58E-03
							7	6501.7	5.58E-03	5903.8	7.09E-04	5251.9	6.13E-03
8	14813	5.96E-03	11773	8.48E-04	14065	6.73E-03
							9	7318.2	5.96E-03	5905.7	1.10E-03	7119.7	6.73E-03
10	14182	6.36E-03	6033.3	1.20E-03	13173	7.37E-03
							11	6499.9	6.36E-03	8296	1.31E-03	14813	7.37E-03
12	6685.4	6.78E-03	6275.7	1.68E-03	39262	7.37E-03
							13	11232	7.23E-03	1230.7	1.83E-03	5038.1	8.07E-03
14	37619	7.23E-03	5906.5	1.83E-03	11399	9.64E-03
							15	11131	7.71E-03	8293	1.83E-03	14505	1.05E-02
16	28633	8.21E-03	11954	1.98E-03	5106.2	1.05E-02
							17	28709	8.21E-03	15211	2.15E-03	11446	1.15E-02
18	6505.1	8.21E-03	5907.1	2.33E-03	20654	1.15E-02
							19	8293	8.74E-03	5910	2.52E-03	39776	1.15E-02
20	14411	9.29E-03	6246.4	2.52E-03	1279.1	1.25E-02
							21	2949.6	9.29E-03	6778	2.52E-03	1293.7	1.25E-02
22	6498.6	9.29E-03	8297.6	2.73E-03	14607	1.25E-02
							23	5942.1	9.88E-03	11526	3.19E-03	5051.9	1.36E-02
24	37067	1.05E-02	6068.9	3.19E-03	7254.9	1.36E-02
							25	5834.9	1.05E-02	5942.1	3.44E-03	11131	1.48E-02
26	6068.9	1.05E-02	8284	3.44E-03	5889.9	1.48E-02
							27	6514.7	1.05E-02	9259.8	4.66E-03	6001.4	1.48E-02
28	5698.7	1.12E-02	8320.8	5.01E-03	6068.9	1.48E-02
							29	9386.5	1.12E-02	11446	5.39E-03	5146.6	1.61E-02
30	1279.1	1.33E-02	11652	5.39E-03	6077.2	1.61E-02
							31	5825.3	1.41E-02	11491	6.23E-03	1290.2	1.74E-02
32	6942.8	1.50E-02	13764	6.23E-03	8284	1.74E-02
							33	5822.4	1.68E-02	6533.4	6.23E-03	5731.4	1.89E-02
34	5824.3	1.68E-02	40894	6.69E-03	8296	1.89E-02
							35	8297.6	1.68E-02	9034.2	6.69E-03	5180.5	2.04E-02
36	5740.9	1.78E-02	14607	7.70E-03	6082.1	2.04E-02
							37	5845.4	1.78E-02	5923	8.84E-03	6202.5	2.04E-02
38	6246.4	1.78E-02	1243	1.01E-02	8293	2.04E-02
							39	8296	1.88E-02	1263.4	1.01E-02	5740.9	2.39E-02
40	28912	1.99E-02	14411	1.01E-02	7410.9	2.39E-02
							41	5743.2	2.11E-02	9482	1.01E-02	14182	2.58E-02
42	6001.4	2.11E-02	23732	1.08E-02	40894	2.58E-02
							43	6033.3	2.11E-02	6157.8	1.08E-02	5750.6	2.58E-02
44	29758	2.22E-02	11399	1.16E-02	5743.2	2.78E-02
							45	8284	2.22E-02	6166.2	1.16E-02	6157.8	2.78E-02
46	28784	2.35E-02	6514.7	1.16E-02	7318.2	2.78E-02
							47	29456	2.35E-02	7143.1	1.16E-02	11232	3.00E-02
48	4106.8	2.35E-02	11131	1.24E-02	8297.6	3.00E-02
							49	5736.4	2.35E-02	33462	1.24E-02	12994	3.23E-02
50	5820.4	2.35E-02	3469.4	1.24E-02	24366	3.23E-02
							51	6275.7	2.35E-02	6505.1	1.24E-02	5583	3.23E-02
52	1293.7	2.48E-02	1238.1	1.32E-02	6218.5	3.23E-02
							53	4873	2.48E-02	14505	1.32E-02	6896.3	3.23E-02

54	5906.5	2.48E-02	24366	1.32E-02	5268	3.48E-02
							55	5923	2.48E-02	6493.9	1.32E-02	5161.5	3.74E-02
56	43045	2.62E-02	6501.7	1.32E-02	6338.3	3.74E-02
							57	5893.5	2.62E-02	1270.7	1.41E-02	77760	3.74E-02
58	5905.7	2.62E-02	23553	1.41E-02	5970.5	4.01E-02
							59	11399	2.76E-02	7254.9	1.41E-02	7358.7	4.01E-02
60	1243	2.76E-02	1287.6	1.50E-02	7453.6	4.01E-02
							61	5898.8	2.76E-02	1222.2	1.60E-02	5604	4.31E-02
62	5910	2.76E-02	12499	1.60E-02	5758.1	4.31E-02
							63	28460	2.91E-02	1290.2	1.60E-02	5893.5	4.31E-02
64	4680.3	2.91E-02	6150.3	1.60E-02	6499.9	4.31E-02
							65	5750.6	2.91E-02	11232	1.70E-02	6505.1	4.31E-02
66	5818.7	3.07E-02	11575	1.70E-02	88472	4.31E-02
							67	5907.1	3.07E-02	4516	1.70E-02	23071	4.62E-02
68	5970.5	3.07E-02	1252.7	1.81E-02	2817.9	4.62E-02
							69	6394.6	3.07E-02	22915	1.81E-02	5226	4.62E-02
70	7049.2	3.07E-02	6499.9	1.81E-02	6166.2	4.62E-02
							71	9158.7	3.07E-02	6942.8	1.81E-02	6493.9	4.62E-02
72	23553	3.23E-02	37619	1.93E-02	6501.7	4.62E-02
							73	28063	3.23E-02	3951.8	1.93E-02	6685.4	4.62E-02
74	5903.8	3.23E-02	3509.1	2.05E-02	4299.1	4.94E-02
							75	10297	3.40E-02	23071	2.18E-02	5868.8	4.94E-02
76	4825.6	3.40E-02	6498.6	2.18E-02	6096.4	4.94E-02
							77	29295	3.58E-02	4508.5	2.32E-02	6109.4	4.94E-02
78	5687.3	3.58E-02	5226	2.32E-02
							79	6077.2	3.58E-02	1293.7	2.46E-02
80	28264	3.76E-02	1304.5	2.46E-02
							81	4508.5	3.76E-02	6077.2	2.46E-02
82	11954	3.96E-02	6202.5	2.46E-02
							83	4633.2	3.96E-02	23110	2.61E-02
84	5765.9	3.96E-02	5868.8	2.61E-02
							85	3552.8	4.16E-02	9669.7	2.61E-02
86	4112.5	4.16E-02	3934.7	2.77E-02
							87	4001.5	4.37E-02	1211.1	2.93E-02
88	5849.4	4.37E-02	3826.7	2.93E-02
							89	6807.4	4.37E-02	4655.1	3.11E-02
90	9259.8	4.37E-02	5797	3.11E-02
							91	9482	4.37E-02	23153	3.29E-02
92	11773	4.59E-02	6184.5	3.29E-02
							93	4547	4.59E-02	1279.1	3.48E-02
94	5657	4.59E-02	23235	3.48E-02
							95	5778.8	4.59E-02	3383.3	3.48E-02
96	5816.4	4.59E-02	5845.4	3.48E-02
							97	6533.4	4.59E-02	7119.7	3.48E-02
98	4104.6	4.82E-02	3813.5	3.68E-02
							99	4836.6	4.82E-02	5849.4	3.68E-02
100	5673.2	4.82E-02	28709	3.89E-02
							101	5731.4	4.82E-02	6807.4	3.89E-02

102	5889.9	4.82E-02	12176	4.11E-02
							103	6184.5	4.82E-02	23182	4.11E-02
104			14182	4.34E-02
							105			3969.4	4.34E-02
106			6087	4.34E-02
							107			5818.7	4.59E-02
108			9759.4	4.59E-02
							109			5811.3	4.84E-02
110			95452	4.84E-02

Table 37

The SELDI biomarker p value of the feature different: H50 chip with baseline

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	9420.3	5.22E-05	11932	5.71E-07	6563.9	5.93E-04
2	6462.8	1.51E-04	12175	2.58E-05	12901	8.46E-04
							3	6660.6	1.51E-04	12386	3.27E-05	3580	1.66E-03
4	9170.7	7.82E-04	12508	7.21E-05	1965.4	1.85E-03
							5	6563.9	8.47E-04	12031	9.97E-05	2943.8	2.53E-03
6	9764	8.47E-04	6889	1.68E-04	6462.8	2.81E-03
							7	6889	9.17E-04	37418	2.77E-04	6889	2.81E-03
8	7366.2	9.17E-04	12088	3.06E-04	19918	3.44E-03
							9	5423.5	9.92E-04	6251.8	3.06E-04	8982.8	3.80E-03
10	9636.5	9.92E-04	12271	3.37E-04	4499.6	4.19E-03
							11	7109.4	1.07E-03	1283.2	7.76E-04	9474.9	4.19E-03
12	28070	1.16E-03	3336.5	7.76E-04	11932	4.61E-03
							13	3705.5	1.16E-03	8982.8	9.26E-04	37418	5.08E-03
14	5317.3	1.83E-03	11779	1.31E-03	7109.4	5.08E-03
							15	9474.9	1.97E-03	3335	1.31E-03	2186.4	6.13E-03
16	14314	2.28E-03	4499.6	1.31E-03	4968.8	6.13E-03
							17	14194	2.45E-03	5171.3	1.31E-03	1000.5	6.73E-03
18	14780	2.63E-03	3335.8	1.42E-03	3488	6.73E-03
							19	1710	2.63E-03	1227.8	1.68E-03	9170.7	6.73E-03
20	28307	2.82E-03	7109.4	1.68E-03	5872.9	8.83E-03
							21	4886.7	3.03E-03	4628.7	1.83E-03	9764	8.83E-03
22	5658.7	3.48E-03	1284.5	1.98E-03	1868.3	9.64E-03
							23	3580	3.73E-03	3342	1.98E-03	2236	9.64E-03
24	7206.6	3.73E-03	11351	2.33E-03	2558.1	9.64E-03
							25	28555	4.28E-03	9474.9	2.52E-03	2944.7	9.64E-03
26	28777	4.28E-03	1270.3	2.73E-03	6660.6	9.64E-03
							27	6209.2	4.28E-03	1239.7	2.95E-03	1234	1.05E-02
28	9584.5	4.28E-03	1276.4	2.95E-03	3449.4	1.05E-02

29	9706.4	4.28E-03	4846.2	2.95E-03	5960.9	1.05E-02
							30	10130	4.58E-03	4994.4	2.95E-03	6852.6	1.15E-02
31	4446.4	4.58E-03	6187.5	2.95E-03	3387.8	1.36E-02
							32	28759	4.89E-03	1265.3	3.19E-03	12386	1.48E-02
33	28825	4.89E-03	5990.8	3.19E-03	3465.1	1.61E-02
							34	9371.9	5.23E-03	9764	3.19E-03	1001.8	1.74E-02
35	9930.7	5.23E-03	3449.4	3.44E-03	2862	1.74E-02
							36	37418	5.58E-03	11626	3.72E-03	6945.7	1.74E-02
37	5890	5.58E-03	1272.6	3.72E-03	9636.5	1.74E-02
							38	1943.8	5.96E-03	1241.2	4.01E-03	11351	1.89E-02
39	2840.2	5.96E-03	1225.5	4.32E-03	20513	1.89E-02
							40	4580.7	5.96E-03	5872.9	4.32E-03	2212.3	1.89E-02
41	4968.8	5.96E-03	1269.2	4.66E-03	5867.8	1.89E-02
							42	12508	6.36E-03	1289.2	4.66E-03	12271	2.04E-02
43	14045	6.36E-03	1258	5.01E-03	2561.9	2.04E-02
							44	12088	6.78E-03	1274.1	5.01E-03	11687	2.21E-02
45	6852.6	6.78E-03	2615.5	5.01E-03	1229.1	2.21E-02
							46	19918	7.23E-03	3420.4	5.01E-03	2088.9	2.21E-02
47	3688.2	7.71E-03	9170.7	5.01E-03	2228.3	2.21E-02
							48	4320.3	7.71E-03	1275.4	5.39E-03	2668.7	2.21E-02
49	57792	7.71E-03	1285.4	5.80E-03	2942.9	2.21E-02
							50	12031	8.74E-03	1286.2	5.80E-03	6251.8	2.21E-02
51	1823	8.74E-03	1290.8	5.80E-03	11053	2.39E-02
							52	4499.6	8.74E-03	1301.2	5.80E-03	12088	2.39E-02
53	4873.9	8.74E-03	9930.7	5.80E-03	7442.3	2.39E-02
							54	9300.5	8.74E-03	1271.3	6.23E-03	9075.3	2.39E-02
55	8937.9	9.29E-03	3915.8	6.23E-03	11090	2.58E-02
							56	12386	9.88E-03	3921.8	6.23E-03	2736.5	2.58E-02
57	28955	1.05E-02	5906.9	6.23E-03	4628.7	2.58E-02
							58	8982.8	1.05E-02	8865.2	6.23E-03	11421	2.78E-02
59	12901	1.12E-02	1332.2	6.69E-03	11445	2.78E-02
							60	5104.1	1.12E-02	4593.6	6.69E-03	11476	2.78E-02
61	8865.2	1.12E-02	5943.2	6.69E-03	12175	2.78E-02
							62	12271	1.19E-02	1287.5	7.18E-03	2605.3	2.78E-02
63	14111	1.19E-02	3919.4	7.18E-03	1003.1	3.00E-02
							64	1794.4	1.19E-02	4613.5	7.18E-03	1005.6	3.00E-02
65	29575	1.19E-02	4744.2	7.18E-03	2220.2	3.00E-02
							66	9334	1.19E-02	6096	7.18E-03	6209.2	3.00E-02
67	2067.7	1.33E-02	1229.1	7.70E-03	6835.6	3.00E-02
							68	1542.1	1.41E-02	1299	7.70E-03	4198	3.23E-02
69	20513	1.41E-02	6209.2	7.70E-03	5658.7	3.23E-02
							70	29140	1.41E-02	1261.7	8.25E-03	2174.5	3.48E-02
71	3922.6	1.50E-02	1262.5	8.25E-03	3567.8	3.48E-02
							72	4628.7	1.50E-02	1317.2	8.25E-03	3571.3	3.48E-02
73	5872.9	1.50E-02	1333.8	8.25E-03	39141	3.48E-02
							74	11932	1.59E-02	3332.4	8.25E-03	1159.5	3.74E-02
75	2186.4	1.59E-02	33454	8.25E-03	12031	3.74E-02
							76	1821.3	1.68E-02	9075.3	8.25E-03	1331	3.74E-02

77	42896	1.68E-02	11421	8.84E-03	4744.2	3.74E-02
							78	5990.8	1.78E-02	4968.8	8.84E-03	9334	3.74E-02
79	12175	1.88E-02	1241.9	9.47E-03	1217.7	4.01E-02
							80	1159.5	1.99E-02	1281.9	9.47E-03	12508	4.01E-02
81	5825.1	1.99E-02	1302.6	9.47E-03	14045	4.01E-02
							82	11132	2.11E-02	1245.3	1.01E-02	2227.1	4.01E-02
83	1985.3	2.11E-02	1292.6	1.01E-02	2772.9	4.01E-02
							84	4603.1	2.11E-02	1330.1	1.01E-02	5825.1	4.01E-02
85	1530.2	2.22E-02	1259.3	1.08E-02	6187.5	4.01E-02
							86	1543.2	2.22E-02	1281	1.08E-02	11132	4.31E-02
87	1796.1	2.22E-02	1314.3	1.08E-02	14780	4.31E-02
							88	2287.8	2.22E-02	2082.2	1.08E-02	1671.3	4.31E-02
89	2944.7	2.22E-02	28555	1.08E-02	1945.6	4.31E-02
							90	4721.4	2.22E-02	1243.4	1.16E-02	2130.5	4.31E-02
91	3024.3	2.35E-02	1256.6	1.16E-02	2132.5	4.31E-02
							92	2634.8	2.48E-02	4141.7	1.16E-02	4185.9	4.31E-02
93	1877	2.62E-02	5731.5	1.16E-02	1000	4.62E-02
							94	1176.7	2.76E-02	5825.1	1.16E-02	1152.8	4.62E-02
95	1528.2	2.76E-02	1236	1.24E-02	11626	4.62E-02
							96	3799.4	2.76E-02	1281.4	1.24E-02	1233	4.62E-02
97	4198	2.76E-02	1737.1	1.24E-02	1330.1	4.62E-02
							98	5906.9	2.76E-02	6168	1.24E-02	1372.8	4.62E-02
99	14510	2.91E-02	8233.8	1.24E-02	15908	4.62E-02
							100	4430.3	2.91E-02	1295.1	1.32E-02	1890.3	4.62E-02
101	4433.9	2.91E-02	8497	1.32E-02	2680.7	4.62E-02
							102	9075.3	2.91E-02	1258.6	1.41E-02	2945.5	4.62E-02
103	10714	3.07E-02	23075	1.41E-02	5943.2	4.62E-02
							104	5761	3.07E-02	1159.5	1.50E-02	7562.2	4.62E-02
105	2491.6	3.23E-02	1315.6	1.50E-02	9420.3	4.62E-02
							106	7282.6	3.23E-02	1331	1.50E-02	11570	4.94E-02
107	8497	3.23E-02	23767	1.50E-02	1190.6	4.94E-02
							108	11490	3.40E-02	2833.4	1.50E-02	2193.3	4.94E-02
109	11594	3.40E-02	11519	1.60E-02	3099.5	4.94E-02
							110	1688.6	3.40E-02	1267.2	1.60E-02	6096	4.94E-02
111	2544.6	3.40E-02	1298.5	1.60E-02	8937.9	4.94E-02
							112	3930.3	3.40E-02	14111	1.60E-02
113	3944.1	3.40E-02	23420	1.60E-02
							114	4335.1	3.40E-02	5658.7	1.60E-02
115	11742	3.58E-02	6087.5	1.60E-02
							116	13942	3.58E-02	1219.8	1.70E-02
117	1755.8	3.58E-02	1234	1.70E-02
							118	1965.4	3.58E-02	1294.7	1.70E-02
119	2833.4	3.58E-02	1296.9	1.70E-02
							120	4185.9	3.58E-02	1733.2	1.70E-02
121	4924.6	3.58E-02	28070	1.70E-02
							122	1281.9	3.76E-02	11132	1.81E-02
123	2630.7	3.76E-02	1237.5	1.81E-02
							124	2788.9	3.76E-02	1321.8	1.81E-02

125	3813.9	3.76E-02	3922.6	1.81E-02
							126	3919.4	3.76E-02	5890	1.81E-02
127	1540.5	3.96E-02	1226.6	1.93E-02
							128	1545.7	3.96E-02	1260.6	1.93E-02
129	1668.9	3.96E-02	3313.1	1.93E-02
							130	3420.4	3.96E-02	11445	2.05E-02
131	4164.9	3.96E-02	11742	2.05E-02
							132	5776.5	3.96E-02	1323.1	2.05E-02
133	11493	4.16E-02	1713.9	2.05E-02
							134	11626	4.16E-02	1823	2.05E-02
135	4994.4	4.16E-02	23106	2.05E-02
							136	5804.3	4.16E-02	4115.8	2.05E-02
137	6251.8	4.16E-02	1778.8	2.18E-02
							138	3921.8	4.37E-02	23126	2.18E-02
139	4189.7	4.37E-02	1278	2.32E-02
							140	11445	4.59E-02	1319.1	2.32E-02
141	11476	4.59E-02	14314	2.32E-02
							142	11494	4.59E-02	1806.3	2.32E-02
143	11779	4.59E-02	3488	2.32E-02
							144	6139.2	4.59E-02	11476	2.46E-02
145	6835.6	4.59E-02	1293.7	2.61E-02
							146	8402.9	4.59E-02	1294.3	2.61E-02
147	1531.8	4.82E-02	1734.9	2.61E-02
							148	1753.2	4.82E-02	23251	2.61E-02
149	2053.4	4.82E-02	4876	2.61E-02
							150	2621.4	4.82E-02	1251.2	2.77E-02
151	2952.6	4.82E-02	1311.6	2.77E-02
							152	4846.2	4.82E-02	15167	2.77E-02
153			1689.8	2.77E-02
							154			2104.6	2.77E-02
155			23145	2.77E-02
							156			5960.9	2.77E-02
157			11490	2.93E-02
							158			11493	2.93E-02
159			11504	2.93E-02
							160			1320.4	2.93E-02
161			1808.7	2.93E-02
							162			3580	2.93E-02
163			40679	2.93E-02
							164			6109.3	2.93E-02
165			6386.4	2.93E-02
							166			8743.7	2.93E-02
167			11494	3.11E-02
							168			1231.9	3.11E-02
169			1264.4	3.11E-02
							170			1295.7	3.11E-02
171			1800.6	3.11E-02
							172			4886.7	3.11E-02

173			11495	3.29E-02
							174			11570	3.29E-02
175			1255.5	3.29E-02
							176			1304.8	3.29E-02
177			1335.3	3.29E-02
							178			1337.3	3.29E-02
179			1762.8	3.29E-02
							180			1782.7	3.29E-02
181			28307	3.29E-02
							182			11560	3.48E-02
183			1300	3.48E-02
							184			1309.4	3.48E-02
185			1309.8	3.48E-02
							186			1310	3.48E-02
187			5867.8	3.48E-02
							188			6139.2	3.48E-02
189			11200	3.68E-02
							190			11537	3.68E-02
191			11568	3.68E-02
							192			1240.9	3.68E-02
193			4126.9	3.68E-02
							194			6047.3	3.68E-02
195			11550	3.89E-02
							196			1254.3	3.89E-02
197			1303.6	3.89E-02
							198			2442.4	3.89E-02
199			3373.2	3.89E-02
							200			5761	3.89E-02
201			1298	4.11E-02
							202			1312.8	4.11E-02
203			1798.8	4.11E-02
							204			2952.6	4.11E-02
205			3557.3	4.11E-02
							206			45039	4.11E-02
207			4873.9	4.11E-02
							208			14194	4.34E-02
209			1760.5	4.34E-02
							210			2963.1	4.59E-02
211			1252.6	4.84E-02
							212			1310.5	4.84E-02
213			1321	4.84E-02
							214			1715.6	4.84E-02
215			1761.1	4.84E-02
							216			2544.6	4.84E-02
217			2816.8	4.84E-02
							218			3853.1	4.84E-02
219			4446.4	4.84E-02
							220			5745.1	4.84E-02

221

9300.5

4.84E-02

Table 38

SELDI biomarker p value: Q10 chip

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	9132	0.001073	1466	0.001011	1209	0.00083
2	7724.8	0.001828	3898.6	0.001011	1310	0.011115
							3	11488	0.002118	4675.2	0.001102	1348.4	0.01598
4	6964.3	0.00263	1167.3	0.001547	4962.1	0.018385
							5	4962.1	0.004576	8918.2	0.001547	2152.4	0.021093
6	4572	0.004893	1335.4	0.001681	1080.1	0.024132
							7	5828.2	0.005962	4512.1	0.001826	1233.1	0.025786
8	13875	0.006785	4632.1	0.001826	2360.3	0.03339
							9	10414	0.007706	1002.3	0.001981	1738.1	0.037845
10	5819	0.008207	6964.3	0.002148	1871.7	0.037845
							11	8918.2	0.008207	1023.6	0.002328	1104.1	0.040251
12	2087.7	0.009883	1197.9	0.002328	2027.6	0.040251
							13	2002.5	0.010504	4361.5	0.002521	1026	0.045445
14	9524.9	0.010504	8674.1	0.003444	1694.3	0.045445
							15	1026.9	0.012578	4962.1	0.004321	11488	0.048242
16	1086.9	0.013343	1151.8	0.005011	1197.9	0.048242
							17	11687	0.019923	1162.9	0.005392
18	2178.4	0.019923	1169.9	0.005392
							19	5858.4	0.019923	5199	0.005797
20	1231.4	0.024804	1008.8	0.006229
							21	1286.6	0.024804	1046.5	0.006229
22	1336.6	0.024804	2421.1	0.006229
							23	2546.3	0.024804	1261.1	0.00669
24	5697.8	0.024804	1619.1	0.007179
							25	1018.1	0.026171	4489.9	0.007179
26	1010	0.027603	5819	0.007701
							27	1330	0.029099	1020.6	0.008254
28	1027.1	0.030664	1003.6	0.008843
							29	3243.2	0.030664	1336.6	0.008843
30	1314.2	0.032299	1159.7	0.009468
							31	1027.3	0.034006	9524.9	0.009468
32	1113.2	0.034006	1137.2	0.01013
							33	1843	0.035789	5828.2	0.010833
34	1056.1	0.037649	1145.9	0.012367
							35	1115.3	0.039588	1179.2	0.012367
36	1036.2	0.041611	1343.5	0.012367

37	1271.3	0.041611	1014.5	0.014086
							38	1652.3	0.041611	1029.5	0.014086
39	1784.6	0.043718	1324.7	0.014086
							40	8202.5	0.043718	4203.8	0.014086
41	1791.8	0.045912	4424.1	0.014086
							42	1297.7	0.048197	1101.3	0.01502
43	4720.4	0.048197	1337.3	0.01502
							44			1001.1	0.018149
45			1834.9	0.018149
							46			1465.5	0.019309
47			6894.9	0.019309
							48			2014.2	0.020532
49			1059	0.02182
							50			1302.2	0.02182
51			1447.4	0.023176
							52			1016.1	0.024604
53			1026.9	0.024604
							54			1038.1	0.024604
55			1157	0.024604
							56			1262.8	0.024604
57			1466.8	0.024604
							58			1018.8	0.026105
59			2918.8	0.026105
							60			1005.3	0.027683
61			1031.8	0.027683
							62			2300.1	0.027683
63			1042.6	0.029341
							64			1126.4	0.029341
65			1142.5	0.029341
							66			1164.9	0.031082
67			1049	0.032909
							68			1318.1	0.034824
69			2016.4	0.034824
							70			1010	0.036832
71			2315.8	0.036832
							72			9132	0.036832
73			1036.2	0.038936
							74			1092.5	0.038936
75			1134.3	0.038936
							76			1159	0.038936
77			1261.7	0.038936
							78			2456.3	0.038936
79			2107.7	0.041138
							80			1017.1	0.043443
81			2247.9	0.043443
							82			1007.2	0.045854
83			1803.2	0.045854
							84			4455.8	0.045854

85			4474.1	0.045854
							86			1010.8	0.048373

Table 39

SELDI biomarker p value: Q10 chip

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	9487.7	2.52E-05	5309.4	0.00054	41779	0.001227
2	9242.4	3.84E-05	3340	0.002521	3357.6	0.006481
							3	8981.3	7.03E-05	12354	0.004655	3803.3	0.01598
4	3424.7	9.42E-05	4997.2	0.006229	3289.9	0.018385
							5	9527.9	0.000114	22360	0.007179	5518.9	0.019699
6	9386	0.000138	5650.4	0.008254	6768.8	0.035559
							7	14058	0.000311	5299.5	0.008843	1454.1	0.045445
8	9078.4	0.000519	5325.1	0.009468	4775.5	0.048242
							9	14777	0.000665	66640	0.013202	89344	0.048242
10	8869.3	0.000847	85778	0.013202
							11	7041.3	0.000917	11759	0.014086
12	8258.7	0.000917	5006.7	0.014086
							13	9019.6	0.000917	5230.5	0.014086
14	8276	0.00116	3245.2	0.01502
							15	7014.2	0.00146	13423	0.016007
16	8281.8	0.00146	5246.4	0.017049
							17	7076.4	0.001968	1454.1	0.018149
18	7060.3	0.002277	5066.1	0.018149
							19	6505.7	0.002448	73372	0.018149
20	6986.9	0.002448	23190	0.019309
							21	8885.9	0.002448	3743.5	0.019309
22	59238	0.00263	5278.1	0.019309
							23	8293.1	0.00263	6049.8	0.02182
24	10017	0.002823	23390	0.023176
							25	27849	0.002823	5020.5	0.023176
26	6489.6	0.00303	6929.1	0.024604
							27	13015	0.00325	3900.8	0.029341
28	6975.9	0.003732	6972.8	0.029341
							29	8302.9	0.003732	6973.4	0.029341
30	5472.3	0.003997	6974.1	0.029341
							31	8288.1	0.003997	80860	0.029341
32	7089.7	0.004576	9242.4	0.029341
							33	14246	0.005229	6965.9	0.031082
34	23190	0.005229	6975.9	0.031082
							35	8327.5	0.005229	11634	0.032909

36	13423	0.005585	1379.7	0.032909
							37	6974.1	0.005585	3182.2	0.032909
38	6950.1	0.005962	4976.1	0.032909
							39	6970.7	0.005962	5088.2	0.032909
40	6973.4	0.005962	6959.8	0.032909
							41	7137.3	0.005962	8281.8	0.032909
42	10354	0.006362	6970.7	0.034824
							43	21192	0.006362	5003.2	0.036832
44	6972.8	0.006362	7060.3	0.036832
							45	8794.2	0.006362	7041.3	0.038936
46	11220	0.006785	71073	0.038936
							47	13906	0.006785	44823	0.041138
48	6496	0.006785	5102.4	0.041138
							49	23390	0.007233	5659.8	0.041138
50	80860	0.007233	5885.5	0.041138
							51	7105	0.008207	6950.1	0.041138
52	6954.2	0.008735	6968	0.041138
							53	7147.5	0.008735	5921.1	0.043443
54	9769	0.009294	5984.7	0.043443
							55	3493.7	0.009883	7266.2	0.043443
56	6687.9	0.009883	13906	0.045854
							57	6968	0.010504	6986.9	0.045854
58	8381.4	0.010504	7014.2	0.045854
							59	6501.9	0.01116	8276	0.045854
60	8238.3	0.01185	3357.6	0.048373
							61	1395.5	0.013343	4479.7	0.048373
62	6477.9	0.013343	7105	0.048373
							63	6527.2	0.013343	8981.3	0.048373
64	6768.8	0.013343
							65	6959.8	0.013343
66	7124.9	0.013343
							67	6965.9	0.014149
68	6698.4	0.014997
							69	6916.5	0.014997
70	6929.1	0.014997
							71	6940.5	0.014997
72	12354	0.015888
							73	28220	0.017807
74	6705	0.01884
							75	6728.4	0.021059
76	6557.6	0.022249
							77	1016.8	0.024804
78	28401	0.024804
							79	41779	0.026171
80	1638.7	0.027603
							81	3760.8	0.027603
82	73372	0.027603
							83	5255.8	0.029099

84	24106	0.030664
							85	5261.4	0.030664
86	66640	0.030664
							87	7169.9	0.030664
88	1403	0.032299
							89	3563.1	0.032299
90	5033.3	0.032299
							91	5054.2	0.032299
92	54069	0.034006
							93	7222.4	0.034006
94	1017.3	0.035789
							95	6484.5	0.035789
96	8425.2	0.035789
							97	89344	0.035789
98	29193	0.037649
							99	5265.3	0.039588
100	6890.8	0.039588
							101	1008.3	0.041611
102	1617.1	0.043718
							103	5042.3	0.043718
104	7240.2	0.043718

Table 40

SELDI biomarker p value: Q10 chip

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	13932	8.33E-06	4651.2	0.000448	2622.4	7.07E-06
2	6983.2	1.47E-05	4652.9	0.000448	1854.3	0.000498
							3	9540.9	3.12E-05	4653.8	0.000448	3220.1	0.000916
4	10319	3.84E-05	1646.7	0.00054	2180	0.001114
							5	9184.1	3.84E-05	4652	0.00054	3338.8	0.001483
6	9468.2	0.000125	4650.5	0.000592	1209.5	0.002146
							7	9652.8	0.000138	4649	0.000848	9103.4	0.003959
8	14136	0.000166	2968	0.001011	1908.8	0.004307
							9	7084.9	0.000182	4976	0.001102	3224.6	0.004307
10	9365	0.000238	11669	0.001423	1637	0.004681
							11	1820.9	0.000311	2960.6	0.001681	3834.7	0.007016
12	13810	0.00037	2773	0.002328	1671.2	0.00759
							13	1714	0.000403	1651.1	0.002521	1891.2	0.008204
14	13917	0.000438	11691	0.003188	2232	0.008204
							15	9919.6	0.000477	4658.3	0.003188	2968	0.008861
16	7060.1	0.000519	23273	0.003717	4100.8	0.009563

17	8853.5	0.000564	3389.5	0.003717	2743.2	0.010314
							18	14018	0.000612	23751	0.004009	1596.6	0.01197
19	1712.5	0.000612	23066	0.004321	1702.9	0.01197
							20	7203.3	0.000612	2558.9	0.004321	1909.7	0.01197
21	13894	0.000665	11565	0.004655	2236.9	0.01197
							22	8807.4	0.000665	11516	0.005392	1620.3	0.01288
23	2191.1	0.000782	4647.3	0.006229	8853.5	0.01288
							24	13947	0.000847	2904.6	0.00669	1621.9	0.01385
25	9103.4	0.000847	11433	0.007701	2409.2	0.01385
							26	6919.9	0.000992	3117.3	0.007701	3793.5	0.01385
27	13959	0.00116	1184.5	0.008843	1597.8	0.014882
							28	14281	0.00116	11862	0.008843	2752.2	0.014882
29	1706.2	0.00116	23471	0.009468	2861.3	0.014882
							30	2176.1	0.00116	4140.8	0.009468	28959	0.014882
31	13985	0.00146	2766.3	0.01013	3110.8	0.014882
							32	14081	0.00146	1633	0.010833	1866.1	0.01598
33	7319.5	0.001697	3313.7	0.011578	2718.2	0.01598
							34	13900	0.001828	2266.2	0.012367	1592.8	0.017146
35	1705.8	0.001828	2765.4	0.012367	2554.3	0.017146
							36	1686.8	0.002118	4973.7	0.012367	1905.1	0.018385
37	13902	0.002277	3347.9	0.013202	1879.8	0.019699
							38	13963	0.002448	46073	0.013202	2960.6	0.019699
39	1928.7	0.00263	9184.1	0.013202	1624.5	0.021093
							40	1192.3	0.002823	3402.1	0.014086	2208.7	0.021093
41	1705.6	0.00303	4332.7	0.014086	3313.7	0.021093
							42	13905	0.00325	4778.6	0.014086	2139.3	0.022569
43	4755.9	0.00325	66483	0.014086	1626.2	0.024132
							44	1707.4	0.003483	9103.4	0.014086	2540.8	0.024132
45	3113.7	0.003483	11727	0.017049	3076.7	0.024132
							46	1737.9	0.003732	1365.9	0.018149	4129.4	0.024132
47	4741.6	0.003732	3256.3	0.018149	9652.8	0.024132
							48	2206.6	0.003997	11484	0.019309	1828	0.025786
49	13828	0.004278	1770.4	0.019309	1595.5	0.027535
							50	13843	0.004576	2547.9	0.019309	1599.6	0.027535
51	8904.5	0.004893	4987.9	0.019309	1618	0.027535
							52	11862	0.005229	1668.7	0.02182	2443.5	0.027535
53	13876	0.005229	1762.9	0.02182	8733.3	0.027535
							54	3544.1	0.005229	1835.7	0.02182	1191	0.029382
55	10132	0.005585	4111.7	0.02182	1568.8	0.029382
							56	11691	0.005585	1970.1	0.023176	17425	0.029382
57	1886.2	0.005585	2876.6	0.023176	10682	0.031332
							58	21103	0.005585	1656.9	0.024604	12908	0.031332
59	1203.3	0.005962	18608	0.024604	1593.6	0.031332
							60	8733.3	0.005962	3391	0.024604	1598.7	0.031332
61	8965.1	0.005962	1652.3	0.026105	1646.7	0.031332
							62	1884.9	0.006362	3000	0.026105	2730.2	0.031332
63	4040.1	0.006362	4379.4	0.026105	3186.7	0.031332
							64	41641	0.006362	11603	0.027683	4728.1	0.031332

65	53658	0.006362	1208.5	0.027683	1591.5	0.03339
							66	1194.9	0.006785	2870	0.027683	1600.9	0.03339
67	13037	0.007233	3170.1	0.027683	2276.1	0.03339
							68	1883.9	0.007233	13917	0.029341	2687.2	0.03339
69	23066	0.007706	3558.7	0.029341	9365	0.03339
							70	39932	0.007706	4376.2	0.029341	1567.6	0.035559
71	4270.6	0.007706	4380.1	0.029341	1633	0.035559
							72	1136.4	0.008207	5232.3	0.029341	4621.6	0.035559
73	7016.5	0.008207	11399	0.031082	8904.5	0.035559
							74	1147.4	0.008735	1648.4	0.031082	11862	0.037845
75	1715.7	0.008735	2640.5	0.031082	1573.8	0.037845
							76	11603	0.009294	4972.6	0.031082	1589.9	0.037845
77	1701.6	0.009883	1655.2	0.032909	3449.9	0.037845
							78	1709.1	0.009883	3236.9	0.032909	1603.7	0.040251
79	1847.5	0.009883	7203.3	0.032909	1641.9	0.040251
							80	1888	0.009883	2553	0.034824	1911.1	0.040251
81	23273	0.010504	4122.7	0.034824	2253.9	0.040251
							82	1190	0.01116	1447.4	0.036832	2898.1	0.040251
83	1005.1	0.01185	2963.4	0.036832	3647.8	0.040251
							84	1153	0.01185	1964.9	0.038936	4140.8	0.040251
85	28959	0.01185	2458	0.038936	1188.8	0.042783
							86	1202	0.012578	13796	0.041138	1570.4	0.042783
87	1832	0.012578	1629	0.041138	1594.6	0.042783
							88	2189.6	0.012578	4378.9	0.041138	3381.2	0.042783
89	4274	0.012578	10880	0.043443	1608.7	0.045445
							90	13781	0.013343	1765.3	0.043443	2773	0.045445
91	9752.3	0.013343	1800.6	0.043443	2550.9	0.048242
							92	1134.5	0.014149	2119.8	0.045854	3213.2	0.048242
93	15011	0.014149	2957.7	0.045854	8807.4	0.048242
							94	1710.8	0.014149	1017.4	0.048373
95	1720.5	0.014149	1089.4	0.048373
							96	1911.1	0.014149	13792	0.048373
97	5018.8	0.014149	1809.1	0.048373
							98	1692	0.014997	2040.5	0.048373
99	4806.2	0.014997	5803.4	0.048373
							100	5138.3	0.014997	8400.5	0.048373
101	6880.3	0.014997
							102	8274.6	0.014997
103	1149.7	0.015888
							104	13792	0.015888
105	3224.6	0.015888
							106	13148	0.016824
107	1717.8	0.016824
							108	1137.8	0.017807
109	1151.9	0.017807
							110	1256.4	0.017807
111	13786	0.017807
							112	13789	0.017807

113	13796	0.017807
							114	1901.4	0.017807
115	11466	0.01884
							116	1696.9	0.01884
117	1700.2	0.01884
							118	7121.4	0.01884
119	1146.3	0.019923
							120	1685	0.019923
121	1724.3	0.019923
							122	1983.3	0.019923
123	3343	0.019923
							124	3766.6	0.019923
125	1679.4	0.021059
							126	1690.3	0.021059
127	1718.6	0.021059
							128	13790	0.022249
129	3014.2	0.022249
							130	3201.4	0.022249
131	3456.1	0.022249
							132	4728.1	0.022249
133	1154.1	0.023497
							134	1167.6	0.023497
135	1727.1	0.023497
							136	7429.4	0.023497
137	10682	0.024804
							138	1765.3	0.024804
139	2519	0.024804
							140	3110.8	0.024804
141	4129.4	0.024804
							142	2749.6	0.026171
143	28290	0.026171
							144	3209	0.026171
145	11433	0.027603
							146	1627.9	0.027603
147	1705.2	0.027603
							148	1762.9	0.027603
149	2631	0.027603
							150	2766.3	0.027603
151	1356.5	0.029099
							152	1629	0.029099
153	1717.3	0.029099
							154	4140.8	0.029099
155	1016.6	0.030664
							156	1133.1	0.030664
157	1148.4	0.030664
							158	1420.8	0.030664
159	1702.9	0.030664
							160	1014.3	0.032299

161	1135.5	0.032299
							162	1150.7	0.032299
163	1199.3	0.032299
							164	1392.9	0.032299
165	2588.8	0.032299
							166	28087	0.032299
167	3574.9	0.032299
							168	4155.8	0.032299
169	6471.6	0.032299
							170	1017.4	0.034006
171	1021.6	0.034006
							172	11669	0.034006
173	1358.8	0.034006
							174	1850.1	0.034006
175	12908	0.035789
							176	1688.5	0.035789
177	2935	0.035789
							178	2992.8	0.035789
179	1125.7	0.037649
							180	1144.6	0.037649
181	1387.5	0.037649
							182	1618	0.037649
183	4272.4	0.037649
							184	1020.1	0.039588
185	1132.2	0.039588
							186	1339.7	0.039588
187	2171.7	0.039588
							188	2898.1	0.039588
189	3438.2	0.039588
							190	4866.1	0.039588
191	77930	0.039588
							192	1018.6	0.041611
193	1139.2	0.041611
							194	1140	0.041611
195	1193.8	0.041611
							196	1257.1	0.041611
197	1670.4	0.041611
							198	1785.8	0.041611
199	1795.8	0.041611
							200	1933.8	0.041611
201	3578.8	0.041611
							202	1142.5	0.043718
203	1599.6	0.043718
							204	1725.6	0.043718
205	2304.4	0.043718
							206	23471	0.043718
207	2803.1	0.043718
							208	1011.1	0.045912

209	1118	0.045912
							210	15376	0.045912
211	2326.1	0.045912
							212	4280.3	0.045912
213	1161.5	0.048197
							214	1304.8	0.048197
215	1340.8	0.048197
							216	1595.5	0.048197
217	2147.1	0.048197

Table 41

The SELDI biomarker p value of the feature different: Q10 chip with baseline

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	2546.3	0.000612	8918.2	0.001681	2477.9	0.001487
2	9132	0.000665	1445.3	0.001826	1209	0.004187
							3	1778.9	0.00146	1466	0.003188	1197.9	0.008071
4	5858.4	0.002448	4424.1	0.004655	9132	0.008071
							5	8918.2	0.00325	1465.5	0.00669	6784.5	0.011475
6	6784.5	0.003732	2280.9	0.007701	4720.4	0.014781
							7	1457.2	0.003997	8674.1	0.008254	8918.2	0.018874
8	1086.9	0.005585	1167.3	0.011578	1348.4	0.020437
							9	1269.5	0.005585	4512.1	0.011578	1444.6	0.020437
10	1445.3	0.005585	6784.5	0.011578	1847	0.023895
							11	1443.4	0.006785	1145.9	0.014086	1871.7	0.023895
12	1746.2	0.007233	1385.2	0.014086	1137.2	0.032305
							13	5772	0.007233	2918.8	0.01502	1393.3	0.032305
14	7724.8	0.008735	1723	0.016007	9524.9	0.032305
							15	1741.6	0.012578	1164.9	0.017049	1179.2	0.034756
16	1486.7	0.013343	1466.8	0.018149	1307.8	0.03736
							17	5697.8	0.014997	1197.9	0.020532	1694.3	0.03736
18	5819	0.014997	1834.9	0.020532	1629.7	0.043054
							19	11488	0.015888	1003.6	0.02182	2288.9	0.046158
20	1784.6	0.015888	1218.6	0.023176	15116	0.049444
							21	9365.8	0.015888	3834.6	0.024604
22	1115.3	0.017807	7090.4	0.024604
							23	1458.5	0.017807	9132	0.024604
24	1660.1	0.01884	1169.9	0.029341
							25	1471.2	0.021059	1463.9	0.029341
26	2002.5	0.023497	1238.7	0.031082
							27	4648.9	0.023497	1652.3	0.031082
28	1210.4	0.024804	9524.9	0.031082

29	1286.6	0.027603	2663.7	0.032909
							30	1500.9	0.027603	5858.4	0.032909
31	6964.3	0.027603	6964.3	0.034824
							32	4572	0.030664	1135.4	0.038936
33	1996.5	0.032299	1067.8	0.045854
							34	1274.2	0.037649	1453.4	0.045854
35	1488.9	0.037649	1343.5	0.048373
							36	6636.1	0.037649
37	1446.1	0.039588
							38	1806.3	0.039588
39	1440.1	0.041611
							40	1500.5	0.041611
41	23326	0.041611
							42	5828.2	0.043718
43	1018.8	0.045912
							44	1231.4	0.045912
45	4675.2	0.045912
							46	9524.9	0.045912
47	16747	0.048197
							48	1838.6	0.048197

Table 42

The SELDI biomarker p value of the feature different: Q10 chip with baseline

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	12354	0.000114	5874.3	0.003444	5518.9	9.47E-05
2	1395.5	0.000917	3182.2	0.004009	1221.1	0.002533
							3	11634	0.000992	12354	0.004321	41779	0.005583
4	8981.3	0.001968	5864	0.005011	3803.3	0.007373
							5	23190	0.002823	11759	0.00669	12354	0.009644
6	10017	0.003483	5896.3	0.00669	1200.1	0.010525
							7	5827.2	0.003483	5902.5	0.007179	5847.2	0.012498
8	23390	0.004576	11634	0.007701	1183.8	0.016052
							9	46588	0.004893	5885.5	0.007701	11634	0.020437
10	5847.2	0.005585	5847.2	0.008843	1355.5	0.023895
							11	5864	0.005962	5957.6	0.01013	3357.6	0.025801
12	6505.7	0.005962	5975.3	0.010833	4885.4	0.027834
							13	23585	0.007233	3900.8	0.01502	51391	0.027834
14	11759	0.007706	3340	0.016007	29193	0.03
							15	5902.5	0.007706	5891.5	0.016007	7997.9	0.03
16	9019.6	0.007706	1454.1	0.017049	8008	0.03
							17	6640.1	0.008207	5937.8	0.017049	4890.3	0.03736

18	6477.9	0.008735	6003.7	0.017049	1120.4	0.040123
							19	9769	0.009294	5993.7	0.019309	11759	0.040123
20	5921.1	0.009883	5947.8	0.020532	1226.4	0.043054
							21	5957.6	0.009883	5827.2	0.023176	5332.9	0.043054
22	3424.7	0.01116	5921.1	0.031082	1100.7	0.046158
							23	6557.6	0.01116	5838.3	0.032909	7650.7	0.046158
24	41779	0.01185	5984.7	0.032909	1125.9	0.049444
							25	24106	0.012578	1459.6	0.038936	5762.4	0.049444
26	6484.5	0.012578	3668.3	0.038936	5792.4	0.049444
							27	6489.6	0.012578	5325.1	0.038936
28	6496	0.012578	5309.4	0.043443
							29	6874.5	0.012578	6049.8	0.043443
30	9078.4	0.012578	5792.4	0.048373
							31	1638.7	0.013343
32	1165.5	0.014149
							33	6501.9	0.014149
34	6853.1	0.016824
							35	1176.8	0.017807
36	6698.4	0.01884
							37	1170.3	0.019923
38	14777	0.019923
							39	5838.3	0.019923
40	5874.3	0.021059
							41	8258.7	0.022249
42	5776.9	0.023497
							43	13015	0.024804
44	6527.2	0.024804
							45	6687.9	0.024804
46	1193.9	0.026171
							47	29193	0.026171
48	6705	0.026171
							49	8276	0.026171
50	1146.1	0.027603
							51	1582.9	0.027603
52	1588.3	0.027603
							53	1617.1	0.027603
54	8281.8	0.027603
							55	11220	0.029099
56	1568	0.029099
							57	6728.4	0.029099
58	1600.7	0.030664
							59	7347.4	0.030664
60	8302.9	0.030664
							61	1179.5	0.032299
62	1399.5	0.032299
							63	5792.4	0.032299
64	5947.8	0.032299
							65	8327.5	0.032299

66	8885.9	0.032299
							67	3743.5	0.035789
68	6890.8	0.035789
							69	1575.8	0.037649
70	5885.5	0.037649
							71	5891.5	0.037649
72	6003.7	0.037649
							73	9386	0.037649
74	6916.5	0.041611
							75	1348.6	0.043718
76	8293.1	0.043718
							77	1167.6	0.045912
78	8288.1	0.045912
							79	3650	0.048197

Table 43

The SELDI biomarker p value of the feature different: Q10 chip with baseline

Matrix (energy)	SPA matrix/(low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	1714	6.37E-05	2968	0.000592	1877.7	0.000281
2	9919.6	8.56E-05	4332.7	0.000776	17425	0.000362
							3	2665.9	0.000261	1749.1	0.001547	1671.2	0.000753
4	8965.1	0.000564	1117	0.002328	1733.1	0.000753
							5	13932	0.000612	1208.5	0.00295	2180	0.001659
6	5138.3	0.00146	3081.9	0.004321	2968	0.001659
							7	9540.9	0.001574	1766.2	0.006229	1714	0.001847
8	1190	0.00263	2291.4	0.006229	4759.9	0.003108
							9	1727.1	0.00303	4111.7	0.006229	6551.3	0.005583
10	1706.2	0.003483	1102.3	0.00669	12908	0.006132
							11	1766.2	0.003483	1103	0.00669	17293	0.007373
12	2588.8	0.003732	4649	0.007179	4956.9	0.008071
							13	9184.1	0.003732	4650.5	0.007179	4242	0.008827
14	1147.4	0.003997	1118	0.007701	1908.8	0.009644
							15	4293.1	0.003997	1123.3	0.007701	1919.3	0.009644
16	8733.3	0.003997	1344.7	0.007701	7429.4	0.009644
							17	9468.2	0.004278	1102.7	0.008843	1701.6	0.012498
18	1148.4	0.004893	1101.3	0.009468	3449.9	0.013598
							19	6551.3	0.004893	1314.9	0.009468	1380.4	0.016052
20	2176.1	0.005229	1475	0.009468	1756.9	0.016052
							21	1913.3	0.005585	1660.4	0.009468	2601.6	0.016052
22	3343	0.005962	1964.9	0.01013	8904.5	0.016052
							23	1159.4	0.006362	1470.9	0.010833	8965.1	0.016052

24	1883.9	0.006362	17293	0.010833	2181.9	0.017414
							25	1117	0.006785	3402.1	0.010833	2420.6	0.017414
26	1142.5	0.006785	11275	0.012367	3076.7	0.017414
							27	1155.4	0.006785	1656.9	0.012367	1241.1	0.018874
28	1795.8	0.006785	2119.8	0.012367	1949	0.020437
							29	13947	0.007233	1099.2	0.013202	4100.8	0.020437
30	4759.9	0.007233	1479.7	0.013202	1792.5	0.023895
							31	2147.1	0.007706	1761.4	0.013202	1986.8	0.023895
32	8274.6	0.007706	1482.7	0.014086	2547.9	0.023895
							33	11862	0.008207	3779.3	0.014086	3343	0.023895
34	1707.4	0.008207	1100.2	0.016007	4806.2	0.023895
							35	1149.7	0.008735	1327.7	0.016007	11466	0.025801
36	1720.5	0.008735	2432.6	0.016007	1905.1	0.025801
							37	1737.9	0.008735	4651.2	0.016007	1847.5	0.027834
38	1709.1	0.009294	4652	0.016007	4621.6	0.027834
							39	2539.2	0.009294	1103.6	0.017049	1225.5	0.032305
40	1132.2	0.009883	1344.2	0.017049	1247.8	0.032305
							41	1785.8	0.009883	1346	0.017049	2086.6	0.032305
42	5018.8	0.009883	1527.4	0.017049	2208.7	0.032305
							43	1118	0.010504	2656.8	0.017049	2261	0.032305
44	11466	0.010504	1097.8	0.018149	1199.3	0.03736
							45	1153	0.010504	1104.7	0.018149	1720.5	0.03736
46	11565	0.010504	1316.1	0.018149	1973.9	0.03736
							47	1712.5	0.010504	1326.7	0.018149	2253.9	0.03736
48	2012	0.010504	1334.6	0.018149	2889.4	0.03736
							49	8853.5	0.010504	1529.3	0.018149	1208.5	0.040123
50	3081.9	0.01116	1751.3	0.018149	1222.9	0.040123
							51	3197.3	0.01116	2355.6	0.018149	1254.5	0.040123
52	12908	0.01185	2765.4	0.018149	1255.6	0.040123
							53	1156.1	0.012578	1116.6	0.019309	3233.6	0.040123
54	1166.2	0.012578	1349.2	0.019309	1352.2	0.043054
							55	1167.6	0.012578	2558.9	0.019309	1660.4	0.043054
56	1391.1	0.012578	1083.6	0.020532	1820.9	0.043054
							57	1742.4	0.012578	1307.1	0.020532	1981.8	0.043054
58	1814.9	0.012578	1526	0.020532	2056.9	0.043054
							59	1820.9	0.012578	1119.6	0.02182	1209.5	0.046158
60	4806.2	0.012578	1499.4	0.02182	1727.1	0.046158
							61	10319	0.013343	1533.4	0.02182	1780	0.046158
62	1725.6	0.013343	1087.7	0.023176	1891.2	0.046158
							63	3220.1	0.013343	1116.2	0.023176	1931	0.046158
64	9752.3	0.013343	1313.7	0.023176	2658.9	0.046158
							65	1116.6	0.014149	17425	0.023176	2861.3	0.046158
66	1160.1	0.014149	2181.9	0.023176	8733.3	0.046158
							67	13810	0.014149	2553	0.023176	1239.8	0.049444
68	1701.6	0.014149	2766.3	0.023176	1270.8	0.049444
							69	4886.6	0.014149	1330.4	0.024604	2319	0.049444
70	1151.9	0.014997	1343.7	0.024604	2409.2	0.049444
							71	1160.9	0.014997	1399.1	0.024604	4122.7	0.049444

72	23066	0.014997	1324.5	0.026105	4364.9	0.049444
							73	1144.6	0.015888	1342.1	0.026105
74	1161.5	0.015888	1510.4	0.026105
							75	1724.3	0.016824	4652.9	0.026105
76	2206.6	0.017807	1084.2	0.027683
							77	1116.2	0.01884	1086.1	0.027683
78	1164.8	0.01884	1532.3	0.027683
							79	2326.1	0.01884	1535.2	0.027683
80	3438.2	0.01884	2326.1	0.027683
							81	4766.1	0.01884	2346	0.027683
82	1121	0.019923	2547.9	0.027683
							83	3766.6	0.019923	3044.6	0.027683
84	11275	0.021059	1298.6	0.029341
							85	2438.8	0.021059	1491.9	0.029341
86	2749.6	0.021059	1733.1	0.029341
							87	7429.4	0.021059	1743.8	0.029341
88	1146.3	0.022249	1767.2	0.029341
							89	1710.8	0.022249	2353.6	0.029341
90	3014.2	0.022249	1297.3	0.031082
							91	3313.7	0.022249	1299.7	0.031082
92	4270.6	0.022249	1325.9	0.031082
							93	1756.9	0.023497	1487.9	0.031082
94	4866.1	0.023497	1526.6	0.031082
							95	1387.5	0.024804	1122.3	0.032909
96	1735.7	0.024804	11565	0.032909
							97	28290	0.024804	11669	0.032909
98	1157.7	0.026171	1256.4	0.032909
							99	1163.7	0.026171	1341.8	0.032909
100	1980.4	0.026171	1481.5	0.032909
							101	5803.4	0.026171	1492.8	0.032909
102	6471.6	0.026171	1501	0.032909
							103	1705.6	0.027603	1086.8	0.034824
104	17425	0.027603	1115	0.034824
							105	1749.1	0.027603	1312.7	0.034824
106	1765.3	0.027603	1496.2	0.034824
							107	2968	0.027603	1531	0.034824
108	4973.7	0.027603	1553.8	0.034824
							109	1327.7	0.029099	1755.5	0.034824
110	1679.4	0.029099	1780	0.034824
							111	1705.8	0.029099	2916.1	0.034824
112	1759.5	0.029099	1461.9	0.036832
							113	1780	0.029099	1467.9	0.036832
114	2443.5	0.029099	1502.7	0.036832
							115	2803.1	0.029099	1085	0.038936
116	46073	0.029099	1262.6	0.038936
							117	4668.4	0.029099	1290.7	0.038936
118	4688.6	0.029099	1294.7	0.038936
							119	1139.2	0.030664	1300.8	0.038936

120	1143.2	0.030664	1462.8	0.038936
							121	13828	0.030664	1469.1	0.038936
122	1436.4	0.030664	1474.1	0.038936
							123	1700.2	0.030664	1509.5	0.038936
124	2832	0.030664	1548.9	0.038936
							125	1122.3	0.032299	1765.3	0.038936
126	1162.5	0.032299	3347.9	0.038936
							127	1119.6	0.034006	5803.4	0.038936
128	1131.8	0.034006	1261.2	0.041138
							129	13148	0.034006	1329.3	0.041138
130	2195.7	0.034006	1518.3	0.041138
							131	4111.7	0.034006	1795.8	0.041138
132	1123.3	0.035789	2754	0.041138
							133	1145.4	0.035789	4653.8	0.041138
134	1767.2	0.035789	1254.5	0.043443
							135	23273	0.035789	1255.6	0.043443
136	28959	0.035789	1308.4	0.043443
							137	4364.9	0.035789	1524.7	0.043443
138	1715.7	0.037649	1547.6	0.043443
							139	2437	0.037649	1106.1	0.045854
140	3201.4	0.037649	1107.6	0.045854
							141	3205.2	0.037649	1521.2	0.045854
142	1115.7	0.039588	1744.6	0.045854
							143	11691	0.039588	2773	0.045854
144	1888	0.039588	3000	0.045854
							145	4280.3	0.039588	1071.7	0.048373
146	1124.5	0.041611	1072.7	0.048373
							147	1877.7	0.041611	1082.9	0.048373
148	2232	0.041611	1114.3	0.048373
							149	2365.9	0.041611	1115.7	0.048373
150	3704.3	0.041611	1192.3	0.048373
							151	1101.3	0.043718	1270.8	0.048373
152	1134.5	0.043718	1279.5	0.048373
							153	1154.1	0.043718	1282.6	0.048373
154	13037	0.043718	1461	0.048373
							155	1717.8	0.043718	1466	0.048373
156	2181.9	0.043718	2429.5	0.048373
							157	3209	0.043718	4647.3	0.048373
158	1136.4	0.045912
							159	1686.8	0.045912
160	1928.7	0.045912
							161	1963	0.045912
162	1981.8	0.045912
							163	2188.4	0.045912
164	4040.1	0.045912
							165	4598	0.045912
166	5867.4	0.045912
							167	8807.4	0.045912

168	2004.9	0.048197
							169	53658	0.048197

Table 44

SELDI biomarker p value: IMAC chip

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	1978.3	0.000339	3240	0.00054	2141.5	0.001629
2	1176.8	0.001253	3301.3	0.001308	1109.8	0.004681
							3	1870.5	0.00325	2330.7	0.001423	2977.4	0.005517
4	2707	0.00325	3233	0.003444	1526.1	0.006481
							5	2483.7	0.004576	3835.3	0.003717	1514.8	0.007016
6	1997.7	0.006785	3341.9	0.004321	5073.2	0.007016
							7	3082	0.008735	3239	0.004655	5806	0.007016
8	1218.9	0.01185	2111.8	0.005011	5673.6	0.008204
							9	1319.2	0.012578	3338.3	0.005797	5883.4	0.008204
10	2977.4	0.013343	2356.3	0.00669	5760	0.009563
							11	1530.1	0.015888	2797.6	0.0Q7701	1110.3	0.01197
12	2691.7	0.015888	3332.7	0.008254	1112.3	0.01385
							13	2572	0.016824	3339.8	0.008254	1124.7	0.01385
14	1768.9	0.017807	3349.5	0.008254	1137.2	0.01598
							15	6959	0.017807	2125.9	0.009468	25550	0.01598
16	1581.5	0.01884	1659.2	0.01013	11114	0.017146
							17	1767.5	0.01884	3844.2	0.01013	1965.7	0.017146
18	2111.8	0.01884	5858.7	0.011578	3028.3	0.017146
							19	2675.9	0.01884	6460.1	0.011578	2386.8	0.018385
20	1483.4	0.019923	2682.3	0.012367	1193.9	0.024132
							21	1702.9	0.021059	6676.8	0.012367	1526.8	0.024132
22	1995	0.023497	6699.1	0.014086	1839.7	0.027535
							23	1494.1	0.024804	1628.4	0.01502	3144.5	0.027535
24	1528.1	0.024804	2572	0.01502	3286.3	0.027535
							25	3338.3	Q.024804	3361.1	0.016007	3658.8	0.027535
26	9534.5	0.026171	2818.4	0.017049	1095.6	0.029382
							27	2038.6	0.027603	4145.4	0.019309	1485.5	0.029382
28	2890.3	0.027603	6440.7	0.019309	1541.6	0.029382
							29	2676.3	0.029099	3222.9	0.020532	1110.8	0.031332
30	1173.6	0.030664	3241.1	0.020532	1816.4	0.031332
							31	2350.6	0.030664	2086.5	0.02182	1072.1	0.03339
32	2785.1	0.030664	6636.9	0.02182	5899	0.03339
							33	4650.5	0.030664	1487.5	0.023176	1108.2	0.035559
34	1159.7	0.032299	5673.6	0.023176	2147.1	0.035559
							35	1485.5	0.032299	1470.9	0.024604	3460.8	0.035559
36	25550	0.032299	2036.4	0.024604	5312.5	0.035559

37	3144.5	0.032299	3324.9	0.024604	1138.6	0.037845
							38	1145.5	0.034006	6959	0.024604	1483.4	0.037845
39	1932.9	0.034006	6648.5	0.026105	1503.6	0.037845
							40	1967.8	0.035789	1483.4	0.027683	1070.2	0.040251
41	4646.1	0.037649	2811.1	0.027683	1094.6	0.040251
							42	1867.9	0.039588	1482.7	0.029341	1128.9	0.042783
43	3151	0.039588	1963.5	0.029341	1528.1	0.042783
							44	3154.1	0.039588	2227.9	0.029341	1084.7	0.045445
45	5893.4	0.039588	6674.2	0.029341	1105.4	0.045445
							46	1293.8	0.041611	1532.1	0.031082	1126	0.045445
47	1408.7	0.041611	2673.5	0.031082	1341	0.045445
							48	1758.2	0.041611	3035.8	0.031082	2824.7	0.045445
49	1920.8	0.041611	3310.3	0.031082
							50	2399.1	0.043718	4191.5	0.031082
51	2804	0.043718	1055	0.034824
							52	2858.4	0.045912	3137.7	0.034824
53	2973.8	0.045912	1191	0.036832
							54	2361.8	0.048197	1403.7	0.036832
55	5673.6	0.048197	5826.7	0.036832
							56	5858.7	0.048197	2970.1	0.038936
57			3279.7	0.038936
							58			1055.5	0.041138
59			2584.2	0.041138
							60			3778.4	0.041138
61			4646.1	0.041138
							62			5914.3	0.041138
63			2223.8	0.043443
							64			3216.8	0.043443
65			4069.6	0.043443
							66			4343.4	0.043443
67			2643.8	0.045854
							68			3313.6	0.045854
69			1054.2	0.048373
							70			2327.6	0.048373
71			2509.2	0.048373
							72			2734.4	0.048373
73			3383.6	0.048373

Table 45

SELDI biomarker p value: IMAC chip

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	9585.6	0.000665	1020.8	0.001547	9248.4	0.001629
2	11505	0.001253	1018	0.007179	6727.5	0.004681
							3	9248.4	0.001253	4032	0.020532	6726.6	0.005084
4	11634	0.002118	6707.7	0.023176	6722.9	0.005982
							5	11530	0.003997	4028.8	0.024604	11287	0.010314
6	9387.3	0.003997	17506	0.027683	6732.5	0.010314
							7	11758	0.005585	4132.2	0.031082	9268.9	0.010314
8	12083	0.005962	4022.3	0.036832	6741.1	0.01197
							9	11611	0.007233	4142.1	0.036832	3184.4	0.01598
10	11652	0.007706	6903.1	0.036832	9601.6	0.01598
							11	11779	0.009883	6688	0.038936	9284.5	0.017146
12	11568	0.010504	6501.1	0.041138	6737.8	0.019699
							13	9284.5	0.010504	4019.9	0.043443	6715	0.024132
14	9384.2	0.01185	6699.1	0.043443	6748.3	0.025786
							15	11437	0.012578	6737.8	0.043443	11342	0.027535
16	9626.4	0.014149	6715	0.045854	9078.3	0.027535
							17	9470.5	0.014997	6741.1	0.045854	6558.5	0.03339
18	11197	0.015888	8950.8	0.045854	10465	0.035559
							19	6189.1	0.015888	1022.7	0.048373	6538.5	0.035559
20	9268.9	0.016824	3740.9	0.048373	9626.4	0.035559
							21	6193.1	0.01884			6756.7	0.040251
22	11040	0.019923			9048.9	0.042783
							23	14017	0.021059			6545.8	0.048242
24	39807	0.024804
							25	9302	0.026171
26	11255	0.029099
							27	2605.4	0.029099
28	6040.4	0.029099
							29	6274.8	0.029099
30	11845	0.030664
							31	5944.5	0.030664
32	11287	0.032299
							33	6067.8	0.032299
34	9516	0.032299
							35	9735.7	0.032299
36	11702	0.034006
							37	5860.6	0.034006
38	5920	0.034006
							39	1225.6	0.037649

40	5910.1	0.037649
							41	74001	0.037649
42	5933.5	0.039588
							43	12381	0.041611
44	7253.8	0.043718
							45	9391.4	0.043718
46	7144.3	0.045912
							47	6252	0.048197
48	7161.6	0.048197
							49	7165.1	0.048197

Table 46

SELDI biomarker p value: IMAC chip

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	1850	0.001353	2570.6	2.91E-05	1229.6	0.009563
2	1191	0.00325	6608.7	0.000306	1001	0.027535
							3	2255	0.003997	3353.8	0.000926	2399.2	0.040251
4	1675.2	0.006362	2115.1	0.003188	33884	0.040251
							5	2203.7	0.007233	6485.2	0.003717	2411.1	0.042783
6	1190.6	0.014149	2079.5	0.00669	2470.1	0.045445
							7	2395.8	0.014149	2622.8	0.007701	3171.9	0.045445
8	2115.1	0.016824	2978.1	0.01013
							9	2036.1	0.01884	6816.7	0.013202
10	3366.4	0.023497	2841	0.014086
							11	13947	0.024804	2819.7	0.01502
12	2472.4	0.032299	1805.5	0.016007
							13	39764	0.034006	1586.1	0.017049
14	3067.3	0.037649	6686.5	0.018149
							15	1191.5	0.041611	2559.4	0.02182
16	1982.7	0.043718	2499.2	0.023176
							17	2407.1	0.045912	2808.3	0.023176
18	2815.1	0.045912	1220	0.024604
							19			1404.8	0.024604
20			1817.6	0.024604
							21			6787.8	0.024604
22			6745.1	0.026105
							23			5005.5	0.029341
24			2807.4	0.031082
							25			2160.8	0.032909
26			3004.7	0.032909
							27			6462.1	0.032909

28			6910.5	0.032909
							29			1600.9	0.034824
30			2685.8	0.034824
							31			3429.6	0.034824
32			1900	0.036832
							33			2770.8	0.036832
34			1611.3	0.038936
							35			1911.5	0.038936
36			4563	0.038936
							37			1242.4	0.041138
38			2157.4	0.041138
							39			1217.6	0.043443
40			6575.1	0.043443
							41			6850.8	0.043443
42			1406.7	0.045854
							43			2826.7	0.045854
44			3740	0.045854
							45			1568	0.048373

Table 47

The SELDI biomarker p value of the feature different: IMAC chip with baseline

Matrix (energy)	CHCA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	1978.3	8.56E-05	3301.3	0.000648	1137.2	0.000144
2	2111.8	0.000665	2111.8	0.001102	1116.5	0.002283
							3	2086.5	0.00116	6648.5	0.001423	1575	0.002533
4	2858.4	0.001353	2673.5	0.002148	1978.3	0.002533
							5	1352.9	0.008735	3233	0.002521	1118.3	0.004187
6	1319.2	0.01185	4145.4	0.002728	2600.9	0.004614
							7	1222.8	0.013343	3240	0.00295	1557.5	0.005583
8	1792.9	0.013343	3008.3	0.004009	4377.2	0.006132
							9	2483.7	0.014149	3239	0.004009	1514.8	0.007373
10	1242.9	0.014997	4726.3	0.004009	1115.3	0.008071
							11	1284.5	0.014997	3259.4	0.004321	1126	0.008071
12	1310.1	0.014997	3213.6	0.008254	1342.1	0.008827
							13	4478.1	0.017807	3835.3	0.008254	1629.8	0.009644
14	1670.7	0.01884	11198	0.008843	1880.2	0.009644
							15	1494.1	0.019923	2223.8	0.01013	4094.2	0.009644
16	1711.1	0.019923	3339.8	0.01013	1642.5	0.010525
							17	2633.5	0.019923	2670.4	0.010833	1102.9	0.011475
18	3082	0.019923	1479.3	0.013202	1117.3	0.012498
							19	2179.4	0.021059	2970.1	0.013202	1128.9	0.012498

20	1288.5	0.023497	2330.7	0.014086	2029.6	0.012498
							21	1917.4	0.023497	3242.5	0.014086	1141.2	0.013598
22	2804	0.023497	3310.3	0.016007	1758.2	0.013598
							23	1642.5	0.024804	6440.7	0.016007	4646.1	0.013598
24	1758.2	0.026171	3137.7	0.017049	1101.3	0.014781
							25	4650.5	0.026171	3241.1	0.018149	2515	0.014781
26	1287.4	0.027603	6460.1	0.018149	1102.5	0.016052
							27	3008.3	0.027603	2589.8	0.019309	1124.7	0.016052
28	1763.1	0.030664	1557.5	0.020532	5673.6	0.016052
							29	1932.9	0.030664	3313.6	0.020532	1851.9	0.017414
30	1842.7	0.032299	1230.1	0.02182	1895.5	0.017414
							31	3349.5	0.032299	13467	0.02182	3717	0.017414
32	1270.7	0.034006	1457	0.02182	1101.8	0.018874
							33	1602.4	0.034006	3460.8	0.02182	1513.8	0.018874
34	1882.1	0.034006	3921.3	0.02182	4639.7	0.018874
							35	1674.7	0.035789	6628.3	0.02182	4657.2	0.018874
36	1723.1	0.035789	1670.7	0.023176	1399.2	0.022109
							37	2964.2	0.035789	1470.9	0.024604	1835.4	0.022109
38	3154.1	0.035789	1610.6	0.024604	1593.9	0.023895
							39	3603.8	0.035789	3242	0.024604	5276.2	0.023895
40	1283.5	0.039588	3246.5	0.024604	2386.8	0.025801
							41	1449.6	0.039588	3315.4	0.024604	1099.2	0.027834
42	2299.2	0.039588	3332.7	0.026105	1121.9	0.027834
							43	1218.9	0.041611	3778.4	0.026105	1685.4	0.027834
44	1500	0.041611	2590.4	0.027683	4643.2	0.027834
							45	1685.4	0.041611	3222.9	0.027683	5073.2	0.027834
46	2174.5	0.041611	3349.5	0.027683	1112.3	0.03
							47	2563.4	0.041611	3844.2	0.027683	1127.4	0.03
48	3714	0.041611	6699.1	0.027683	1094.6	0.032305
							49	4657.2	0.045912	3496.8	0.029341	1222.8	0.032305
50	1995	0.048197	3954.8	0.029341	1576.7	0.032305
							51			5858.7	0.029341	1628.9	0.032305
52			2036.4	0.031082	1878.1	0.032305
							53			4191.5	0.031082	1109.8	0.034756
54			5338.2	0.031082	1169.8	0.034756
							55			5673.6	0.031082	1862.2	0.034756
56			6959	0.031082	1108.2	0.03736
							57			1674.7	0.032909	1121.1	0.03736
58			2074.3	0.032909	1139.8	0.03736
							59			4377.2	0.034824	1630.6	0.03736
60			1691.3	0.036832	1111.4	0.040123
							61			2734.4	0.036832	1892.2	0.040123
62			3717	0.036832	2141.5	0.040123
							63			4596.2	0.036832	2250.2	0.040123
64			6674.2	0.036832	4441	0.040123
							65			1820.2	0.038936	1105.4	0.043054
66			2078	0.038936	1110.3	0.043054
							67			3216.8	0.038936	1168.4	0.043054

68			3338.3	0.038936	1541.6	0.043054
							69			22302	0.041138	1573.5	0.043054
70			3724.9	0.041138	1503.6	0.046158
							71			14006	0.045854	1518.2	0.046158
72			1844.8	0.045854	1572.3	0.046158
							73			2572	0.045854	1826.2	0.046158
74			4646.1	0.045854	2107.2	0.046158
							75			6636.9	0.045854	1457	0.049444
76			6663.7	0.045854	1459.2	0.049444
							77			1503.6	0.048373	1573	0.049444
78			2682.3	0.048373	1932.9	0.049444
							79			3595.6	0.048373	4072.9	0.049444
80			7008.2	0.048373	6631	0.049444

Table 48

The SELDI biomarker p value of the feature different: IMAC chip with baseline

Matrix (energy)	SPA matrix (high-energy)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	11505	0.000151	1020.8	0.006229	1002.4	0.018874
2	11530	0.001253	12247	0.007701	11040	0.022109
							3	11634	0.001828	1250.2	0.016007	3184.4	0.023895
4	11568	0.001968	3925	0.019309	9339.7	0.025801
							5	11779	0.002448	3920.5	0.031082	4118.5	0.043054
6	12083	0.002448	11530	0.038936	1000.7	0.046158
							7	12247	0.002448	11758	0.038936	13170	0.046158
8	2605.4	0.00263	11779	0.038936	11568	0.049444
							9	3103.1	0.003997	11505	0.041138	7765.9	0.049444
10	11652	0.004278	28285	0.041138	7772.9	0.049444
							11	11702	0.004278	11702	0.043443
12	11758	0.004278
							13	11611	0.004576
14	12381	0.005229
							15	11845	0.005585
16	9104.1	0.01116
							17	2800.5	0.022249
18	6826.1	0.022249
							19	6827.9	0.022249
20	1182	0.029099
							21	10246	0.039588
22	6377.8	0.043718
							23	11437	0.045912

Table 49

The SELDI biomarker p value of the feature different: IMAC chip with baseline

Matrix (energy)	SPA matrix (low-yield)
							Sample:	0 hour time		24 hours time		48 hours time
Ion number	m/z	p	m/z	p	m/z	p
							1	2646.6	0.001073	2622.8	0.001981	2880.4	0.000362
2	1675.2	0.00146	1198.6	0.003444	2523.9	0.003436
							3	11571	0.001574	11571	0.004655	1920.1	0.011475
4	1850	0.002823	1217.9	0.005011	2244.9	0.012498
							5	2871.7	0.004576	1242.4	0.006229	2808.3	0.017414
6	2036.1	0.006362	11751	0.007179	1881.6	0.020437
							7	2448.2	0.007706	1361	0.011578	1024.6	0.022109
8	11751	0.009883	1217.6	0.012367	3171.9	0.025801
							9	2034.2	0.014997	3165.4	0.013202	4108.7	0.025801
10	2472.4	0.016824	1543.9	0.014086	31457	0.034756
							11	1235.7	0.017807	2363.5	0.016007	1141.4	0.043054
12	2160.8	0.017807	1287.6	0.017049	1642.2	0.046158
							13	2221.3	0.019923	2978.1	0.018149	3004.7	0.046158
14	5993.7	0.021059	2559.4	0.019309	11571	0.049444
							15	2407.1	0.023497	1920.1	0.020532	2214.6	0.049414
16	1817.6	0.024804	1560.6	0.02182	2434.1	0.049444
							17	2484.8	0.024804	1003.8	0.023176
18	2203.7	0.026171	1220	0.024604
							19	2255	0.026171	1292.4	0.024604
20	5866.1	0.030664	1360	0.024604
							21	2053.3	0.032299	1318.4	0.027683
22	3345.6	0.032299	2841	0.029341
							23	2214.6	0.034006	1288.9	0.031082
24	2028.6	0.037649	1379.4	0.032909
							25	2062.1	0.037649	1261.6	0.034824
26	2719.1	0.037649	1270.4	0.034824
							27	1230.7	0.045912	1301.7	0.034824
28	9645.7	0.045912	1586.1	0.034824
							29			1805.5	0.034824
30			1005.7	0.038936
							31			1244	0.038936
32			2118	0.038936
							33			1832.1	0.041138
34			2059.5	0.041138
							35			3212.4	0.041138
36			1260.7	0.043443
							37			3572.4	0.043443
38			1257.3	0.045854
							39			1259.5	0.045854

40			2214.6	0.045854
							41			2570.6	0.045854
42			2880.4	0.045854
							43			1284.4	0.048373

Described as embodiment 1.4.5 (as preceding), listed SELDI analytical data is implemented the MART analysis among the his-and-hers watches 26-49.Table 50 has shown two SELDI result of experiment that obtain from time 0 sample, and wherein Fen Lei accuracy is satisfied or surpassed about 60%.

Table 50

The MART of SELDI data analyzes

Time (hour)	Chip type	Matrix	Laser energy	Sensitivity	Specificity	Accuracy	Mark (m/z)
								0	H50	CHC A	Low	67％	64％	65％	9297.4
0	Q10	SPA	Low	88％	76％	82％	9540.9，6983.2， 9184.1，1928.7， 3000

With reference now to some representative embodiment and details, described the present invention fully, technician in the field it is evident that, can change and modify and do not deviate from herein the spirit or scope of the present invention that proposes these the present invention.

Claims (90)

1. determine the method for septicopyemia state in the individuality, this method comprises:

(a) first biological sample that obtains from this individuality certainly obtains first biomarker spectrum; With

(b) first biomarker spectrum with described individuality compares with the reference biomarker spectrum that obtains from reference colony;

Wherein once this comparison just can be classified as this individuality and belong to or do not belong to this reference colony, and wherein this relatively determines the septicopyemia state in this individuality.

2. determine the method for septicopyemia state in the individuality, this method comprises:

(a) obtain first biomarker spectrum at single time point from this individuality; With

(b) first biomarker spectrum with described individuality compares with reference biomarker spectrum;

Wherein the comparison of this biomarker spectrum is to determine the septicopyemia state in this individuality at least about 60% accuracy.

3. determine the method for septicopyemia state in the individuality, this method comprises composes (i) relatively from first biological sample that obtains from this individuality at single time point first biomarker spectrum that produces and the reference biomarker that (ii) produces from reference colony, wherein this relatively comprises the application decision rules, and this decision rules is determined the septicopyemia state in this individuality.

4. determine the method for septicopyemia state in the individuality, this method comprises:

(a) first biological sample that obtains from this individuality certainly obtains first biomarker spectrum; With

(b) the reference biomarker spectrum that first biomarker of described individuality spectrum and biological sample from reference colony are obtained relatively,

Wherein reference colony is selected from normal reference colony, the positive reference of SIRS-colony, the negative reference of infected/SIRS-colony, the positive reference of septicopyemia colony, be in the reference colony of septicopyemia developmental stage, after about 0-36 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, after about 36-60 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, with the positive reference of the SIRS-colony that after about 60-84 hour, confirms to suffer from septicopyemia by routine techniques, and wherein once this comparison just can be classified as this individuality and belong to or do not belong to this reference colony, and wherein this relatively determines the septicopyemia state in this individuality.

5. determine the method for septicopyemia state in the individuality, this method comprises that first biomarker spectrum that first biological sample that (i) obtained from this individuality certainly produces and the biomarker spectrum that (ii) obtains from the biological sample of reference colony are relatively, wherein this relatively is classified as this individuality and belongs to or do not belong to this reference colony, and wherein this has relatively determined the septicopyemia state in should individuality.

6. determine the method for septicopyemia state in the individuality, this method comprises:

(a) select at least two kinds of features in one group of biomarker from first biomarker spectrum that first biological sample from this individuality produces; With

(b) this feature is compared with one group of identical biomarker the reference biomarker spectrum that produces from the biological sample from reference colony,

Wherein once such comparison just can belong to or not belong to this reference colony at least about 60% accuracy this individuality is classified as, and wherein this relatively determines the septicopyemia state in this individuality.

7. determine the method for septicopyemia state in the individuality, this method comprises:

(a) determine the abundance of at least two kinds of biomarkers from first biomarker spectrum that first biological sample from this individuality obtains or the variation of abundance; With

(b) in first biomarker spectrum that should individuality the abundance of these at least two kinds of biomarkers or abundance change with compose from the reference biomarker of reference colonial organism sample in the abundance of these biomarkers or the variation of abundance compare,

Wherein this comparison can be classified as this individuality and belong to or do not belong to this reference colony, and wherein this has relatively determined the septicopyemia state in should individuality.

8. determine the method for septicopyemia state in the individuality, this method comprises with the positive reference colony of the SIRS-that suffers from septicopyemia from (i) and the abundance or the abundance variation of at least a biomarker of reference biomarker spectrum of biological sample of (ii) not suffering from the positive reference of the trouble SIRS-colony of septicopyemia compares, abundance or the abundance of determining at least a biomarker from first biomarker spectrum that first biological sample from this individuality obtains change, and wherein biomarker is selected from listed biomarker in arbitrary table of showing 15-23 and 26-50.

9. the method for claim 2, wherein individual first biomarker spectrum be from first biological sample of this individuality, and the biological sample that obtains since reference colony of reference biomarker spectrum.

10. each method of claim 1 and 3-9, wherein biological sample is selected from blood, saliva, serum, blood plasma, urine, ight soil, cerebrospinal fluid, cell, cell extract, tissue sample and biopsy.

11. the method for claim 1, it also comprises:

(a) second biological sample that obtains from this individuality obtains second biomarker spectrum; With

(b) second biomarker spectrum that should individuality and reference biomarker spectrum relatively,

Wherein this comparison second time can be classified as this individuality and belong to or do not belong to this reference colony, and wherein should relatively determine the state of septicopyemia in this individuality for the second time.

12. each method of claim 1 and 3-9, it comprises also and repeats this method at least once that wherein independent biomarker spectrum independent biological sample from this individuality when this method repeats at every turn obtains.

13. the method for claim 12, wherein the biological sample that obtains from this individuality is with the collection in about 24 hours of being separated by.

14. each method of claim 1-8, the state of wherein determining septicopyemia in this individuality comprises the outbreak of septicopyemia in this individuality of prediction.

15. the method for claim 14 is wherein using routine techniques to determine in this individuality before the septicopyemia outbreak at least about 24 hours prediction septicopyemias.

16. the method for claim 14 is wherein using routine techniques to determine in this individuality before the septicopyemia outbreak at least about 48 hours prediction septicopyemias.

17. the method for claim 14 is wherein using routine techniques to determine in this individuality before the septicopyemia outbreak of predicting septicopyemia at least about 96 hours.

18. each method of claim 1-8 determines that wherein the state of septicopyemia in this individuality comprises the development of determining septicopyemia in this individuality.

19. each method of claim 1-8, the state of wherein determining septicopyemia in this individuality comprises the septicopyemia in this individuality of diagnosis.

20. each method of claim 1-2 and 4-8, wherein this relatively comprises the application decision rules.

21. the method for claim 3 or 20 is wherein used decision rules and is comprised use data analysis algorithm.

22. the method for claim 21, wherein the data analysis algorithm comprises the use classification tree.

23. the method for claim 21, wherein the data analysis algorithm is a distribution free.

24. the method for claim 23, the difference during wherein data analysis algorithm detected characteristics value distributes.

25. the method for claim 24, wherein nonparametric algorithm comprises the signed rank test of use Wilcoxon.

26. the method for claim 21, wherein the data analysis algorithm comprises the multiple regression tree that adds up of use.

27. the method for claim 21, wherein the data analysis algorithm is a logistic regression.

28. the method for claim 21, wherein the data analysis algorithm comprises at least two input parameters.

29. the method for claim 28, wherein the data analysis algorithm comprises at least five input parameters.

30. the method for claim 29, wherein the data analysis algorithm comprises at least ten input parameters.

31. the method for claim 30, wherein the data analysis algorithm comprises at least 20 input parameters.

32. the method for claim 21, wherein the data analysis algorithm uses table 15-23 and 26-50 at least two kinds of features shown in any as input parameter.

33. the method for claim 20, wherein decision rules is to determine the state of septicopyemia in the individuality at least about 60% accuracy.

34. the method for claim 33, wherein decision rules is to determine the state of septicopyemia in the individuality at least about 70% accuracy.

35. the method for claim 34, wherein decision rules is to determine the state of septicopyemia in the individuality at least about 80% accuracy.

36. the method for claim 35, wherein decision rules is to determine the state of septicopyemia in the individuality at least about 90% accuracy.

37. the method for claim 33, wherein use routine techniques determine this individuality suffer from the clinical signs of suspected of septicopyemia before at least about the state of determining septicopyemia in this individuality in 48 hours.

38. the method for claim 33, wherein decision rules is subjected to ten times of cross validations.

39. each method of claim 1-8, wherein the reference biomarker obtains from the colony of containing single individuality.

40. each method of claim 1-8, wherein reference biomarker spectrum obtains from the colony of containing two individualities at least.

41. the method for claim 40, wherein reference biomarker spectrum obtains from the colony of containing 20 individualities at least.

42. each method of claim 1-3 and 5-8 is wherein from being selected from normal reference colony, the positive reference of SIRS-colony, the negative reference of infected/SIRS-colony, the positive reference of septicopyemia colony, be in the reference colony of septicopyemia developmental stage, after about 0-36 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, after about 36-60 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, obtain reference biomarker spectrum with the colony of the positive reference of the SIRS-that after about 60-84 hour, confirms to suffer from septicopyemia by routine techniques colony.

43. each method of claim 1 and 3-9, it comprises that also with from second biomarker spectrum of individuality and reference biomarker spectrum relatively, wherein this second biomarker spectrum obtains from second biological sample that picks up from this individuality.

44. the method for claim 43 was wherein gathered this second biological sample from this individuality in about 24 hours after gathering first biological sample from this individuality.

45. the method for claim 43 wherein compares second biomarker spectrum and the reference biomarker spectrum that is different from first biomarker spectrum.

46. each method of claim 1 and 3-9, first biomarker spectrum that wherein should individuality and reference biomarker spectrum comprise the detectable aspect of at least a nucleic acid.

47. the method for claim 46, its amplifying nucleic acid is mRNA.

48. each method of claim 1-8, but first biomarker spectrum and reference biomarker that wherein should individuality be composed the context of detection that contains at least a polypeptide.

49. the method for claim 48, but the detection of wherein said context of detection comprises at least a polypeptide is contacted with antibody or its function fragment of this at least a polypeptide of specific combination.

50. the method for claim 49, wherein said antibody or its function fragment can be detected ground mark.

51. the method for claim 50, wherein this mark is the nucleic acid that can increase.

52. the method for claim 49, wherein this at least a polypeptide is present in the blood.

53. the method for claim 49, wherein this at least a polypeptide is a cell surface protein.

54. the method for claim 49, wherein this at least a polypeptide is the cause of disease component.

55. the method for claim 49, wherein this at least a polypeptide is the antibody in conjunction with the cause of disease component.

56. the method for claim 49, wherein this at least a polypeptide is an autoantibody.

57. each method of claim 1 and 3-9, this method comprise the protein from this individuality gained biological sample is contacted with antibody array, wherein the antibody of this array is fixed.

58. each method of claim 1 and 3-9, wherein before described first biomarker spectrum that obtains described individuality with described biological sample fractional separation.

59. each method of claim 1-8, wherein at least a separation method are used to obtain first biomarker spectrum of described individuality.

60. the method for claim 59, wherein at least two kinds of separation methods are used to obtain first biomarker spectrum of described individuality.

61. the method for claim 59, wherein said at least a separation method comprises mass spectrum.

62. the method for claim 61, wherein said mass spectrum are selected from electrospray ionization mass spectrometry (ESI-MS), ESI-MS/MS, ESI-MS/ (MS) ⁿ, desorb/ionization (DIOS) on the auxiliary laser desorption ionisation flight time mass spectrum of matrix (MALDI-TOF-MS), surperficial laser enhanced desorb/ionization time of flight mass spectrometry (SELDI-TOF-MS), silicon, secondary ion massspectrum (SIMS), four utmost point flight time (Q-TOF), atmospheric pressure chemical ionization mass spectrum (APCI-MS), APCI-MS/MS, APCI-(MS) ⁿ, normal atmosphere Photoionization Mass Spectrometry (APPI-MS), APPI-MS/MS, and APPI-(MS) ⁿ, four-electrode spectrum, Fourier transform mass spectrum (FTMS) and ion trap mass spectrometry, wherein n is the integer greater than 0.

63. the method for claim 62, wherein at least a separation method comprises SELDI-TOF-MS.

64. the method for claim 59, wherein at least a separation method is selected from chemical extraction distribution, ion exchange chromatography, anti-phase liquid chromatography(LC), isoelectrofocusing, one dimension polyacrylamide gel electrophoresis (PAGE), two-dimentional polyacrylamide gel electrophoresis (2D-PAGE), thin-layer chromatography, gas chromatography, liquid chromatography (LC) and their arbitrary combination.

65. the method for claim 59 wherein uses at least two kinds of different separation methods to obtain the biomarker spectrum of described individuality.

66. each method of claim 1-8, first biomarker spectrum and the described reference biomarker of wherein said individuality are composed the detectable aspect that contains infectious agent or its component.

67. the method for claim 66, wherein said component is selected from virus capsid protein, lipopolysaccharides and lipoteichoicacid.

68. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker are composed the context of detection that contains biomarker, and the state that this biomarker is replied infection for immunity system provides information.

69. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker spectrum contain the context of detection of biomarker, and this biomarker is selected from hormone, autoantibody, somatomedin, transcription factor, cell surface marker and derives from the soluble protein of cell.

70. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker are composed the context of detection that contains the biomarker relevant with microbemia.

71. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker are composed the context of detection that contains the biomarker relevant with the scavenger cell cracking.

72. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker are composed the context of detection that contains the biomarker relevant with the septicopyemia approach.

73. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker are composed the context of detection that contains autoantibody.

74. each method of claim 1-8, but first biomarker of wherein said individuality spectrum and described reference biomarker spectrum contain the context of detection of biomarker, described biomarker be selected from tissue hypoxia, multiple organ dysfunction is unusual, and is relevant with the physiological situation of metabolic acidosis.

75. the method for septicopyemia outbreak in the prediction individuality, this method comprises:

(a) aspect of at least two kinds of features in the detection of biological mark spectrum, wherein this biomarker spectrum contains at least two kinds of biomarkers that are selected among the biomarker group listed among one of table 15-23 and 26-50; With

(b) relatively, with the value of the corresponding aspect of at least two kinds of identical in the aspect that is detected of described at least two kinds of features and reference colony features

Wherein once this comparison just can be classified as this individuality and belong to or do not belong to this reference colony, and wherein this comparison prediction should individuality in the outbreak of septicopyemia.

76. the method for claim 75, the prediction of wherein said septicopyemia outbreak was made in septicopyemia outbreak precontract in 12-36 hour, and wherein the outbreak of septicopyemia is determined by routine techniques.

77. the method for claim 75, the prediction of wherein said septicopyemia outbreak was made in septicopyemia outbreak precontract in 36-60 hour, and wherein the outbreak of septicopyemia is determined by routine techniques.

78. the method for claim 75, the prediction of wherein said septicopyemia outbreak was made in septicopyemia outbreak precontract in 60-84 hour, and wherein the outbreak of septicopyemia is determined by routine techniques.

79. the method for SIRS in the diagnosis individuality, this method comprises:

(a) first biological sample that obtains from this individuality certainly obtains first biomarker spectrum; With

(b) first biomarker spectrum with described individuality compares with the reference biomarker spectrum that obtains from reference colony,

Wherein once this comparison just can be classified as this individuality and belong to or do not belong to this reference colony, and the SIRS of this comparative diagnoses in should individuality wherein.

80. the method for SIRS in the diagnosis individuality, this method comprises:

(a) obtain the biomarker spectrum at single time point from this individuality; With

(b) described individual biomarker spectrum is compared with the biomarker spectrum,

Wherein the comparison of this biomarker spectrum can be to diagnose the SIRS in the individuality at least about 60% accuracy.

81. the method for SIRS in the diagnosis individuality, this method comprises: (i) composed relatively from first biological sample first biomarker spectrum that produces and the reference biomarker that (ii) produces from reference colony of this individuality collection at single time point, wherein this relatively comprises the application decision rules, and this decision rules is determined the state of SIRS in this individuality.

82. the method for SIRS in the diagnosis individuality, this method comprises:

(a) first biological sample that obtains from this individuality certainly obtains first biomarker spectrum; With

(b) first biomarker spectrum of described individuality is composed relatively with the reference biomarker of the biological sample that obtains from reference colony,

Wherein reference colony is selected from normal reference colony, the positive reference of SIRS-colony, the negative reference of infected/SIRS-colony, the positive reference of septicopyemia colony, be in the reference colony of septicopyemia developmental stage, after about 0-36 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, after about 36-60 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, with the positive reference of the SIRS-colony that after about 60-84 hour, confirms to suffer from septicopyemia by routine techniques, wherein once this comparison just can be classified as this individuality and belong to or do not belong to this reference colony, and the SIRS of this comparative diagnoses in should individuality wherein.

83. the method for SIRS in the diagnosis individuality, this method comprise comparison (i) but from first biological sample that this individuality certainly obtains obtain first biomarker spectrum and the biomarker spectrum that (ii) obtains from reference colony gained biological sample between the detected characteristics of at least a biomarker, wherein relatively this individuality is classified as and belongs to or do not belong to this reference colony, and wherein this comparative diagnoses should individuality in SIRS.

84. the method for SIRS in the diagnosis individuality, this method comprises:

(a) select at least two kinds of features in one group of biomarker from the biomarker spectrum that first biological sample from this individuality produces; With

(b) this feature is compared with one group of identical biomarker the biomarker spectrum that produces from the biological sample from reference colony,

Wherein once such comparison just can belong to or not belong to this reference colony at least about 60% accuracy this individuality is classified as, and the SIRS of this comparative diagnoses in should individuality wherein.

85. the method for SIRS in the diagnosis individuality, this method comprises:

(a) determine the abundance of at least two kinds of biomarkers obtaining from first biological sample or the variation of abundance from this individuality; With

The abundance of the biomarker in (b) should the biological sample of individuality or abundance change and compare from the abundance of these biomarkers in the biological sample of reference colony,

Wherein this comparison can be classified as this individuality and belong to or do not belong to this reference colony, and the SIRS of this comparative diagnoses in should individuality wherein.

86. the method for SIRS in the diagnosis individuality, this method comprises with changing from the abundance of at least a biomarker of the biological sample of normal reference colony or abundance compares, determine that wherein biomarker is selected from listed biomarker in arbitrary table of showing 15-23 and 26-50 from the abundance or the abundance variation of at least a biomarker that obtains from this individual biological sample.

87. the method for separating bio mark, wherein said biomarker can be used for producing the biomarker spectrum with diagnosis or prediction septicopyemia, described method comprises:

(a) obtain reference biomarker spectrum, described reference biomarker spectrum obtains from the colony of individuality;

(b) identify the feature of described reference biomarker spectrum, wherein said feature can prediction or one of stage of diagnosis of sepsis or septicopyemia;

(c) evaluation is corresponding to the biomarker of described feature; With

(d) separate described biomarker.

88. contain the biomarker spectrum of at least two kinds of features, wherein based on the comparison of reference colony, described at least two kinds of features help to belong to reference colony at least about 60% accuracy individuality is classified as, and wherein this reference colony is selected from normal reference colony, the positive reference of SIRS-colony, the negative reference of infected/SIRS-colony, the positive reference of septicopyemia colony, be in the reference colony of septicopyemia developmental stage, after about 0-36 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, after about 36-60 hour, confirm to suffer from the positive reference of the SIRS-colony of septicopyemia by routine techniques, with the positive reference of the SIRS-colony that after about 60-84 hour, confirms to suffer from septicopyemia by routine techniques.

89. test kit, it contains at least two kinds of biomarkers in the listed biomarker in any table that is selected from table 15-23 and 26-50.

90. test kit, it contains and the one group of antibody or its function fragment that are selected from two kinds of biomarker specific combination of listed biomarker in any table of showing 15-23 and 26-50 at least.

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